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If you want to speak with Matt Meuli’s firm directly for a one-on-one pre-consult, call:

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Disclaimer: This conversation is educational and should not be treated as legal, tax, financial, estate planning, Medicaid, asset protection, or fiduciary advice for your specific situation. Matt is an attorney, but he is not your attorney unless and until you formally engage his firm.

The Conversation Gen X Can’t Keep Avoiding

There is a strange anxiety sitting inside the Gen X household right now. It is not the old anxiety of inheritance. It is not simply the question of who gets what when Mom and Dad are gone.

It is more practical than that. More exhausting. More administratively brutal.

It is the quiet fear that one day soon, possibly without warning, someone will have to untangle the entire family operating system — and the person expected to do it may be the same Gen Xer already trying to raise kids, fund college, keep a business alive, keep a marriage steady, help aging parents, manage their own retirement math, and decode a world that keeps getting more expensive and more digital at the same time.

That is the emotional center of this week’s Matt Chats conversation between Chris Snook and Matt Meuli. On the surface, it is another Wednesday office-hours session inside the Shields & Succession column. But underneath the legal language, trust terminology, phone numbers, Medicaid questions, and asset protection structures is a much more human story.

It is the story of the generation that learned to adapt before anyone ever gave them credit for it.

Gen X drank from garden hoses.

Gen X came home when the streetlights turned on.

Gen X learned technology before their parents and before their kids.

Gen X survived analog childhood, digital adulthood, the dot-com bubble, 9/11, the housing crash, the Great Financial Crisis, endless platform shifts, a pandemic, and now the age of AI.

And now Gen X is being asked to adapt again. This time, the problem is not a new device, a new platform, a new market cycle, or a new operating system on a laptop.

It is the family operating system.

Who has authority?

Who knows where the documents are?

Who can access the bank accounts?

Who has the passwords?

Who knows what the care plan is?

Who knows what Mom and Dad own?

Who talks to the doctors?

Who pays the bills?

Who coordinates the siblings?

Who protects the assets?

Who prevents the avoidable mess from becoming the family’s next chapter?

That is why this episode matters. Because for a lot of Gen X families, the silent worry is not, “What will I inherit?” It is, “What disaster am I going to have to administer?”

Three favors as you listen

1. Hit the ❤️. The algorithm is a slot machine and hearts are quarters.

2. Hit the 🔄 restack. Somebody in your network is two weeks into the beach, watching stocks wiggle, wondering what they were created to do. Get them up.

3. Hit 📤 share. You know exactly one person who needs to start the daily phone call before it’s too late. Send them the Interlude.

Share

Bonus Credit: Drop a comment. Tell me your bucket-of-apples moment, the lesson somebody pointed at you before you were ten. I read every one, and I reply to the ones that make me laugh, make me think, or make me money. Preferably all three.

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The Bathroom Story That Explains Everything

Matt opens the conversation with a story that sounds almost too ordinary to be important.

That is exactly why it is important.

At one point in his own life, Matt had an older family member living in the house, teenage boys under the same roof, several adults trying to function, and not enough bathrooms. He woke up one morning and confronted the kind of problem that no estate planning diagram fully captures.

He needed a bathroom. Not eventually. Not conceptually. He needed it that morning.

So he went to a real estate app, searched for houses with four or more bathrooms, and within a month, bought one. It is funny because it is human. It is also not really about bathrooms. It is about what happens when caregiving stops being an idea and becomes a floor plan.

Families do not experience aging parents as a legal category. They experience them as someone who needs a room, a ride, a meal, a medication schedule, help with bills, a safe shower, a working phone, and someone who knows what to do when a facility costs $10,000 a month, and no one is sure what assets are available.

Estate planning sounds formal. Caregiving is physical. Asset protection sounds strategic. Aging parents need help getting through Tuesday.

That is the power of Matt’s story. It compresses the whole Gen X sandwich-generation problem into one scene: too many people, too few bathrooms, too many responsibilities, and not enough of a plan.

The story also gives the conversation credibility. Matt is not only speaking as an attorney who has seen clients navigate these problems. He is speaking as someone who has lived the squeeze himself. He knows what it feels like to be working full-time, raising children, helping older family members, and trying to make decisions when the information is incomplete.

That is what makes Matt Chats work. It is not theory wearing a suit. It is real experience translated into legal and practical questions that families can actually use.

The Difference Between Being Nosy and Being Prepared

One of the most important distinctions in the episode is the difference between being nosy and being prepared. This is the emotional choke point for adult children.

Most Gen Xers do not want to interrogate their parents. They do not want to sound entitled. They do not want to imply that Mom or Dad is incompetent. They do not want to ask about bank accounts, wills, trusts, passwords, insurance, care preferences, advisors, or power of attorney documents in a way that sounds like they are quietly counting the inheritance before anyone has died.

But politeness can become dangerous when it turns into avoidance.

If a parent falls, breaks a hip, develops cognitive decline, gets scammed, needs memory care, or can no longer manage bills, the adult child who was too polite to ask may suddenly be the adult child expected to solve everything. Matt’s framing is simple.

Lead with help. Not control. Not entitlement. Not inheritance.

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In Part I of this series, I argued that the most valuable asset in wealth management is no longer Assets Under Management (AUM).

It’s owning the client relationship when intelligence becomes free. That statement may sound provocative until you consider what is actually happening around us. For decades, advisors competed on access. Access to information. Access to products. Access to managers. Access to planning expertise. Access to institutional knowledge.

Today, nearly all of those advantages are being compressed, and the fees associated with those advantages have and will fall accordingly.

Artificial intelligence can summarize a prospectus. Analyze a balance sheet. Compare investment strategies. Generate planning scenarios. Draft communications. Review tax considerations. Organize estate planning documents. And increasingly, do it faster than most humans.

This does not mean advisors become obsolete. It means advisors must become something different. The profession is approaching one of those rare moments where technology changes not only how work gets done, but what clients ultimately value.

The advisors who win the next decade will not be the ones who use AI to produce more reports. They will be the ones who use AI to create more trust.

Not because trust can be automated. Because everything surrounding trust can be. That distinction may become the defining competitive advantage of the Intelligence Economy.

Three Favors Before You Keep Reading

1. Hit the ❤️.

The future of advice won’t be won by the firms with the biggest technology budgets. It will be won by the firms that learn fastest. Every heart helps this idea reach another advisor, attorney, CPA, trustee, or family office leader trying to make sense of what comes next.

1. Hit the 🔄 restack.

Somebody in your network is still thinking AI is a software story.

It’s not. It’s an operating model story. It’s a trust story. It’s a client relationship story.

And it’s a story that will determine who owns the service layer of wealth management over the next decade. Share this with the advisor, compliance officer, CPA, attorney, or business owner who needs to see around that corner before everyone else does.

1. Hit 📤 share.

You know at least one professional who’s asking the question privately but hasn’t said it out loud yet:

“If AI can do more of the work, where does my value come from?”

Send them this article. The answer may be more encouraging—and more profitable—than they realize.

Share

Then drop a comment.

What’s one workflow in your business you’d automate tomorrow if compliance, security, and trust weren’t obstacles?

Or tell me where you believe the future moat really lives:

Trust? Context? Taste? Coordination?

I read every comment. I especially love the ones that challenge my assumptions, sharpen the thesis, or reveal something the rest of us haven’t seen yet. Now, let’s get back to the future of advice.

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The Great Misunderstanding About AI

Most firms are treating AI like a software upgrade. That is the wrong framework. Software helps people work faster. AI changes who—or what—does the work. That is a completely different shift.

The internet changed communication. Cloud computing changed infrastructure. AI is changing labor itself.

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For decades, the wealth management industry has measured success using a simple scorecard. Assets Under Management (AUM). AUM became the proxy for trust. The proxy for scale. The proxy for enterprise value. The proxy for influence. The proxy for success. The seed ingredient for fee generation.

Entire firms were built around gathering assets. Entire compensation systems were designed around gathering assets. Entire acquisitions roll-up strategies were valued around gathering assets.

But every industry eventually reaches a moment when the metric it optimized for stops telling the whole story.

I believe wealth management is approaching that moment now. Don’t get me wrong, AUM still matters, and the data shows that total AUM will continue to grow at a CAGR of 10.9% through 2032, but the continued fragmentation of the industry and confusion over how to best implement a compliant AI strategy, workflow improvements, and retain the downstream generational relationships that will direct that AUM beyond 2032, is the bigger and more important story.

Because for the first time in modern history, intelligence itself is becoming abundant. And when something becomes abundant, something else becomes scarce.

The firms that understand what is becoming scarce will define the next era of advice, hold off fee compression forces, and build the premium value firm with a strong moat optionality in the years to come.

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Three favors before you continue

Hit the ❤️. The algorithm is a slot machine, and hearts are its quarters.

Hit the 🔄 restack. Somebody in your network is two weeks into the beach, watching stocks wiggle, wondering what they were created to do. Get them up or their advisor up to speed.

Hit 📤 share. You know exactly one person who needs to start the daily phone call before it’s too late. Send them the Interlude.

Share

Drop a comment. Tell me your “aha” moment, or the lesson somebody taught you about the future when you were ten. I read every one, and I reply to the ones that make me laugh, make me think, or make me money. Preferably all three. Now, let’s get you back to your regularly scheduled program.

Leave a comment

The Last Time This Happened

When the internet arrived, information became abundant. Before the internet, advisors possessed a genuine information advantage.

• Research reports.

• Market data.

• Economic analysis.

• Industry intelligence.

Access itself created value. Then the information became free. The advisors who survived weren’t the ones who possessed information. They were the ones who provided interpretation (The sensemakers).

Then the mobile web arrived. It was at this point that access became free. Again, value shifted.

Then cloud computing arrived. Infrastructure became abundant and cheap, unlocking scale. Again, value shifted.

Now, AI is creating another shift. This time, the scarce resource isn’t information, access, or infrastructure…It’s intelligence. The ability to summarize. Analyze. Compare. Draft. Research. Model. Reason. And recommend.

Tasks that once required highly trained knowledge workers are becoming increasingly accessible. Not because humans became smarter. Because intelligence became cheaper.

That changes everything.

The Wrong Question

Most advisors are asking:

Will AI replace advisors?

That is the wrong question. The better questions are:

When intelligence becomes commoditized, what remains valuable?

How do we rewire our workflows, operational stack, and team members to deliver uniquely against that new value shift?

What need states will our human customers still have, and what frees us up to spend the majority of our time filling those needs better than any alternative?

Who ultimately “owns” the client experience in our business? Us or our vendor stack? What parts must we “own” and what do we happily “rent”, and how do we stay nimble and tool agnostic?

Because history suggests the answer is never the thing being commoditized. It is the layer above it. For instance:

When information became abundant, interpretation became valuable.

When access became abundant, experience became valuable.

When intelligence becomes abundant, trust becomes valuable. So does context. So does Taste. So does coordination.

Those four assets (trust, context, taste, and coordination) may become the most valuable assets in wealth management.

Not portfolios. Not planning software. Not investment models. Not research.

Trust. Context. Taste. Coordination.

Why the Industry Is Looking the Wrong Way

Most AI conversations today focus on tools. ChatGPT. Claude. Copilot. Agents. Automation. Prompting. Productivity. Those conversations matter.

But they miss the bigger story.

AI is not primarily a software revolution. It is a labor and workflow revolution.

For the last few decades, The $7-rule has applied. Businesses spent one dollar on software and roughly six dollars on people, implementation, administration, consulting, operations, compliance, support, coordination, and execution.

The software market was (and always has been) smaller than the services market. Much smaller.

The reason investors are so excited about AI, isn’t because AI creates better software. It’s because AI may begin absorbing portions of the service layer.

That means every advisory firm should be asking:

Who owns the service layer once intelligence becomes abundant?

Because whoever owns that layer may own the client relationship and the lion’s share of the fees that come along with it.

The Real Asset Was Never the Portfolio

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Subscribe to James Bulltard

This conversation is for experienced traders, active investors, financial professionals, family offices, advisors, and market participants who understand that markets are not moved only by stories.

They are moved by flows. By levels. By positioning. By machines. By institutions. And most importantly…

By the difference between knowing a company is good and knowing where the trade actually is.

DISCLAIMER: This episode is educational and should not be treated as investment, trading, financial, legal, or tax advice. Always do your own research, and talk with your advisor before putting any real money on the line. Options trading involves substantial risk and is not appropriate for every investor. Do your own diligence, understand your own risk tolerance, and consult a qualified professional before acting.

TL;DR Key Takeaways

James Bulltard is one of the most unusual finance voices on Substack because he has built the highest-conversion “paid community” on around transparency, options flow, technical levels, and a blunt refusal to waste people’s time.

He began learning markets as a kid on Yahoo message boards in the 1990s, long before FinTwit, Discord, Substack, or AI-powered workflows existed.

His early market education came the hard way: buying names, losing money, getting his teeth kicked in, and eventually having someone explain technicals in a way that made the whole game click.

His core operating belief is that a chart either looks good or it does not. That does not mean fundamentals do not matter. It means timing, levels, flows, and price action matter deeply when someone is trying to trade, rather than simply “own” for decades.

James is not a day trader in the frantic sense. He says he rarely makes moves and is highly calculated when he does.

The 21 EMA, or 21-day exponential moving average, is central to his framework. In his view, when a name or index is above the 21 EMA, traders can press. When it breaks below, short-term risk changes.

He keeps his charts simple: 8 EMA, 21 EMA, 50-day, 100-day, and 200-day moving averages.

James believes every stock is a buy somewhere on the chart. The mistake many investors make is believing every good stock is a buy at every level.

His edge is not merely options data. All options data comes from the same core source. His edge is how he filters it, manually logs what he finds relevant, and applies a rules-based process to identify trades that matter.

He personally logs roughly 150 to 160 relevant trades per day, then uses his database and AI to build better trade structures around the institutional flows he sees.

He does not see AI as replacing his judgment. He uses it to scale his rules and apply his parameters across more names than he could manually analyze alone.

His community includes roughly 2,500 people in Discord, including traders across a wide range of account sizes and a meaningful number of finance professionals.

He openly shares his book, entries, exits, and positioning, which he believes is one of the reasons his community trusts him.

The mission began in 2022 with a desire to level the playing field for retail investors who were getting bad information from online “furus” claiming magical entries and exits without real transparency.

His view of the market is simple but not simplistic: institutions leave footprints, machines trade levels, and the individual trader’s job is to stop guessing and start reading where the largest players are actually acting.

The deeper story is that James Bulltard is both avatar and human: a private person who keeps his face offscreen, but has built trust by showing the thing most finance personalities hide.

The book.

Why You Should Listen

This ATOMIQ LEVEL conversation with James Bulltard is not just a trading interview.

It is a rare look inside the operating system of a private trader who has built one of the most compelling paid finance communities on Substack by doing the opposite of what most internet market personalities do.

He does not lead with lifestyle theater. He does not sell certainty. He does not pretend every chart is a mystery. He does not waste time dressing up a weak setup with a good story.

He opens the book. He shows the work. He lets the market judge.

James came up in the old world of Yahoo message boards, where the internet was rougher, slower, and less performative, but still full of the same human impulses that define markets today: greed, fear, ego, hope, confusion, conviction, and the painful education of losing money before learning what the tape is actually saying.

That is where his worldview started. Not in a polished institutional training program. Not in a bank analyst class. Not in a YouTube course. In the messy early internet, as a kid trying to understand why stocks moved and why his own trades kept going wrong.

Then someone taught him technicals. And it clicked.

Three decades later, he has turned that original click into a rules-based workflow that combines moving averages, institutional options flow, manual filtering, AI-powered database analysis, and a Discord community full of people who want one thing:

An edge.

The conversation matters because it sits at the intersection of several powerful themes at once: retail access, institutional footprints, AI leverage, trust as a moat, Substack as a business model, and the difference between being a market commentator and being someone whose actual trades can be seen.

It is also a conversation about humility in a strange form.

James is blunt, sometimes brutally so. He will tell people that if they cannot make money with the information he is putting in front of them, maybe this game is not for them. But beneath the bluntness is a deeper respect for the market. He is not pretending the market owes anyone anything. He is saying the data is there, the levels are there, the flow is there, and the individual trader has to decide whether they are willing to learn how to read it.

Press play on this episode if you want to understand why one anonymous avatar has become one of the most effective paid finance publishers on Substack, how he thinks about the 21 EMA, why he believes options flow offers a live view into institutional intent, and how AI is letting one human’s rules scale across a market that never stops moving.

Because in James Bulltard’s world, the chart either looks good or it does not.

And the tape does not care about your story.

The Avatar Who Opened the Book

James Bulltard, Data Driven Puts, and the Trust Moat Behind One of Substack Finance’s Fastest-Rising Voices

Before James Bulltard became one of the most compelling finance voices on Substack, before the Discord community, before the database, before the AI workflows, before the paid subscribers, before the MarketStack rankings, before the avatar became a recognizable presence inside the finance ecosystem, he was a kid on the Yahoo message boards.

That detail matters.

Because before there was FinTwit, before there was Substack, before there were influencer threads, Discord rooms, algorithmic feeds, live options dashboards, and AI copilots, there were message boards full of strangers trying to figure out the same old game.

What is moving?

Who knows something?

Why did this stock break?

Why did this one run?

Why did I buy it right before it fell?

James was young, curious, and interested in stocks before he fully understood what he was doing. Like many early market obsessives, he learned first through pain. He bought things. He lost. He got his teeth kicked in. He did not yet understand why some stocks were strong, why others were weak, why a good company could still be a bad trade, or why conviction without timing can become very expensive.

Then somebody reached out and explained technicals.

And something in him clicked.

Not partially.

All at once.

From that point forward, James began seeing the market differently. A chart was no longer just a picture of where price had been. It became evidence. It became a visual expression of buying, selling, pressure, strength, weakness, positioning, and probability.

That is the first key to understanding James Bulltard. He is not trying to make markets mystical. He is trying to make them readable.

The Bluntness Is the Brand

There is a reason James’s subscribers respond to him. He does not waste time.

In his own words, a chart either looks good or it does not.

That bluntness is not a performance gimmick. It is part of the operating system. James is not interested in spending twenty minutes explaining why a stock should go higher if the chart is already saying something else. He has very little patience for the kind of market commentary that dresses up uncertainty with confidence or turns every setup into a narrative.

That is why this conversation becomes useful quickly. Chris frames the tension between two investing temperaments: the fundamental investor who wants to own great businesses for the long haul, and the technical trader who understands that a great business is not always a great investment at every price.

James does not reject the idea that great companies can compound over time. In fact, he says it does not take a rocket scientist to know that buying great companies like Amazon or Google can work over long stretches.

But that is not the hard part. The hard part is knowing when the name is strong. When it is weak. When to press. When to step aside.

When the short-term trade has changed, even if the long-term story still sounds beautiful. That is where technicals matter. That is where James lives.

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The 21 EMA as the Line in the Sand

Every serious market participant eventually develops a few lines they trust more than others.

For James, one of those lines is the 21 EMA.

The 21 exponential moving average is, in his words, the most important moving average in the market. He describes it as roughly the one-month moving average and treats it as a short-term risk barometer. When a name, index, or setup is above the 21 EMA, he believes there is room to press. When it breaks below, the trader has to start asking what comes next.

He is careful enough to note that most breaks below the 21 EMA do not become catastrophes. Often, the market saves itself a day or two later.

But every major sell-off begins with weakness somewhere. And for James, the break under the 21 EMA is the warning light.

That simplicity is part of the appeal. He is not building a carnival of indicators. He keeps five moving averages on the chart: the 8 EMA, the 21 EMA, the 50-day, the 100-day, and the 200-day.

Short-term barometers. Longer-term structure. Price, flow, and levels.

The deeper idea is not that a moving average is magic. It is that markets are now dominated by computers, algorithms, and institutions that react to levels. The machines are not sitting around reading balance sheets. They are not debating a stock’s long-term brand value. They are buying and selling through programmed levels, triggers, risk controls, liquidity, and momentum.

If you are trading shorter timeframes, James argues, you have to think like the computers.

Because if the machines are trading levels and you are trading feelings, you are playing a different game than the one actually happening.

Every Stock Is a Buy Somewhere

One of the more important ideas in the conversation is deceptively simple.

Every stock is a buy somewhere on the chart.

That does not mean every stock is good. It does not mean every stock should be owned. It does not mean every price is justified.

It means location matters.

This is where James’s worldview becomes useful even for listeners who are not active options traders. The buy-and-hold investor can still learn from the idea that entry matters. The family office can still learn from the idea that position timing changes risk. The advisor can still learn from the idea that markets are not only about what to own, but when to own it, how to size it, and when to stop forcing a story against deteriorating price action.

A great company can be a bad trade. A hated name can become attractive at the right level. A crowded winner can become dangerous below the wrong line. A broken stock can still bounce.

The question is not only, “Is this good?”

The question is, “Where is the trade?”

That is the shift.

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The Book as the Moat

James’s rise on Substack did not come from being the loudest finance personality online. It came from transparency.

He says plainly that what made him different was that he was probably one of the first people to actually share his book.

That sentence is the heart of the story.

During the COVID-era explosion of online trading commentary, everyone had opinions. Everyone had screenshots. Everyone had Excel sheets. Everyone seemed to be magically in and out of positions at exactly the right time. The internet was full of people selling confidence, claiming wins, and rarely showing enough detail for anyone to verify the process.

James looked at that landscape and saw a problem.

Retail investors were getting a bad deal.

Too many people were selling the appearance of market competence without showing the evidence that would let a subscriber decide whether the person was actually doing what they claimed.

So James chose a different route.

Show the entries.

Show the exits.

Show the book.

Let people see the volume.

Let them decide.

That transparency became trust.

And trust became the moat.

Chris points this out directly in the conversation. James may not have a traditional institutional moat. Other people can access options data. Other people can use AI. Other people can build dashboards. But not everyone can build the kind of earned trust that comes from four years of showing the work in public.

James’s answer is even simpler. His moat is himself.

The Discord as a Trading Floor

The Discord community is its own character in this story.

James describes it as a world of its own, with roughly 2,500 people inside. Some are trading small books. Others send screenshots of enormous sessions. Many are finance professionals. Some are experienced active traders. They come from different walks of life, but they are there for the same reason.

They want an edge.

James does not pretend the community is designed for absolute beginners who need every term explained from scratch. He is straightforward about that. His work is better suited for people who already understand trading enough to know what they are looking at and want the relevant information filtered into a simple, usable format.

That honesty matters. Not every product is for everyone. Not every community should be beginner-friendly. Not every trading room needs to pretend it can turn anyone into a professional.

James is building for people who can act on an edge if the edge is put in front of them.

And his Discord community gives them something that feels less like a newsletter and more like being a fly on the wall of a live market process.

The Substack is the front door. The Discord is the room where “it” happens.

The Database That Watches the Footprints

The most interesting part of James’s system is not simply that he watches options flow.

Lots of people watch options flow. His distinction is how he filters it.

All options data ultimately comes from the same core source. James does not pretend otherwise. The edge is not in claiming access to magical data no one else can see. The edge is in knowing which trades matter, which ones to ignore, how to classify them, how to log them, and how to build better trades around them.

Each day, James personally logs roughly 150 to 160 trades he considers relevant. This is not fully automated. He is looking through the tape. He has parameters. He has a helper. He has rules. But the judgment is still human.

That is important.

In an era where everyone wants to automate everything, James is not removing himself from the loop. He is placing himself exactly where he believes his judgment matters most: deciding which footprints are worth recording.

Then the database does the next layer of work. It helps build better trades off the institutional flow. The raw trade is not the final trade. It is the clue.

Data Driven Puts

One of the clearest examples comes from put sales.

James explains that when a large institution wants to build a position, it may sell a large amount of puts at a level where it would be willing to own the stock. That put sale is not random noise. It may represent the end result of meetings, analyst work, portfolio manager decisions, risk review, and institutional positioning.

To James, that matters.

A large fund willing to own millions of shares of a company at a specific price is leaving a footprint. The individual trader does not need to pretend to know more than the institution.

The individual trader can ask a better question:

Can I build a better trade around that footprint?

James says someone in his community ran an analysis across thousands of put sales he had logged over several years, and a large majority expired worthless. For a put seller, that is the desired outcome. The nuance is important: he is not saying all put sales have that result. He is talking about the ones he flagged as unusual and relevant.

That is where the database becomes powerful. If the large put sale itself has historically carried attractive probabilities within James’s filtered universe, then building a lower, more conservative put sale around that same institutional footprint may improve the setup even more.

This is the James Bulltard operating system in miniature.

1. See the institution.

2. Respect the level.

3. Filter the data.

4. Build the better trade.

Do not guess when the tape is showing you where serious money may be willing to act.

AI as a Force Multiplier, Not a Replacement

The AI part of the conversation is especially relevant for the ATOMIQ LEVEL audience.

James is not using AI as a personality replacement. He is not asking the model to become the trader. He is using AI to scale his rules.

That distinction also matters.

He has a rule set for how he views options data. He manually logs what he believes matters. He has years of observed behavior. He knows what he wants the system to examine. AI allows him to apply those parameters across more names, more structures, and more potential trades than he could highlight manually each day.

Before, he might pick five trades a day that he found most interesting. Now, the same parameters can be applied across the broader database.

That is the practical version of human-plus-machine. The human supplies the taste, judgment, filtering, parameters, and context.

The machine supplies the scale.

This is where the conversation becomes about more than trading. It becomes about the future of expertise. James has codified part of his own pattern recognition into a process that can be extended with AI, but the thing being scaled is still his judgment.

That is why the moat is not only the tools. The moat is the human, whose rules, the tool is scaling.

The Live View Versus the Delayed Report

One of James’s sharpest points is his disdain for stale information.

He contrasts live options flow with 13F filings, which show institutional holdings after the fact. By the time most people are studying those filings, the information may already be months old. The trade may have changed. The thesis may have shifted. The hedge may be different. The position may no longer represent what outsiders think it represents.

Options flow, in James’s view, gives a more immediate view.

Not perfect. Not omniscient. Not guaranteed. But live.

If large players are buying puts, selling puts, buying calls, or structuring trades in size, those trades can reveal where institutions are acting now, not where they were positioned last quarter.

That is why James is less interested in storytelling and more interested in the tape. The market leaves clues. Most people just do not know which clues to care about.

The Business of Trust

Jame’s Substack growth story is almost as interesting as the trading story.

James has built a simple funnel. Free subscribers come in through Substack. Paid subscribers receive access to the Discord and a daily recap with market analysis, highlighted names, a database link, and his open book. He sends out an expiring daily database link because the app and Substack are not directly integrated.

It is not overcomplicated. It is not bloated. It is not trying to be everything to everyone. It is a paid relationship built on the belief that the subscriber will receive more value than the monthly price.

James is not shy about that. He charges for value and tells people directly that if they cannot make more than the subscription costs using the amount of information he provides, they may need to find a different hobby.

That may sound harsh.

But in the context of his audience, it is part of the promise. He is not selling comfort. He is selling a filtered edge to people who are supposed to know what to do with one.

That is also why his conversion rate matters. Chris highlights that MarketStack had identified James as one of the strongest finance performers on Substack, not simply because of raw free-subscriber scale, but because his paid conversion performance was extraordinary relative to far larger publications.

That says something important about the future of independent financial media.

Trust converts.

Proof converts.

Utility converts.

Specificity converts.

A faceless avatar can outperform polished media brands if the audience believes the value is real and sees the avatar putting his own money on the line and driving substantial returns consistently.

The Trading Book and the Life Book

There is a revealing moment when James talks about how people should think about money.

He distinguishes between long-term investments and a trading book. He has long-term investments that he does not check often because they are long-term. Then he has trading capital, where the rules are different.

This distinction is essential.

James is not telling people to turn their entire financial life into a casino. He is saying that trading capital should be treated differently from long-term wealth. It should be money someone can afford to lose. It should have its own rules. It should not be confused with retirement capital, core assets, or money needed for life obligations.

That idea may be uncomfortable for some traditional wealth audiences, but it is also clarifying.

Do not pretend your trading book is your family’s long-term financial plan.

Do not pretend your long-term portfolio is a short-term trading account.

Do not use one framework for money that needs different jobs.

That is a Wealth Matters 3.0 ethos at its core. Capital has different roles, each driving towards different matters of wealth in your life and portfolio. Confusing those roles is where trouble begins.

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Active Case Study: The Intel Example

The Intel trade becomes the episode’s recurring case study.

James explains that Intel had become one of the hottest names in his database, seeing far more activity than other names. That gave him the conviction to put on a large risk reversal and later a deep-in-the-money call spread. He describes the structure, the strikes, the decay, and why he was not panicking even when the broader market looked weak.

The lesson is not “copy this trade.”

The lesson is his process. He had observed the flow. He ranked the activity. He saw repeated institutional interest. He built the structure. He understood the remaining upside and downside. He knew the conditions under which he would continue to hold.

That is what experienced traders do. They do not simply say, “I like Intel.”

They define the structure. They know the levels. They understand the time decay. They know what still has to happen. They understand where the trade can still work even if the stock moves against them.

For listeners who do not trade options, the mechanics may be advanced. But the principle is simple.

A trade is not an opinion. A trade is a structure.

The Private Man Behind the Avatar

One of the more human elements of the episode is the format itself.

James appears as an avatar. The audience hears his voice but does not see his face. Chris makes clear that this is not a technical error. It is intentional. James is a private person, and the show respects that.

That privacy makes the trust story more interesting, not less.

In a media world obsessed with face, polish, video clips, lifestyle, and personal branding, James has built a high-trust financial community while remaining visually hidden.

That should make every creator and advisor pay attention. The future of media is not only about showing more of yourself. Sometimes it is about showing the right thing.

James does not show his face. He shows his book.

And for his audience, that may matter more, because his book is way sexier than any man could ever be.

The Father Behind the Trader

Near the end of the conversation, another layer appears.

James talks about family. Chris connects it to his own memory of a father who was present, who played catch after school, who may not have been a massive earner but gave something many children do not get enough of: time.

James’s own workday ends when the market closes. That gives him something rare in high-intensity finance: the ability to be present for his kids in a way that matters to him.

That may seem like a small detail after an hour of moving averages, put sales, call spreads, AI models, and options flow.

It is not small.

It may be the detail that explains why this conversation belongs on Wealth Matters 3.0 and why the ATOMIQ LEVEL understanding and acceptance of oneself is the ultimate level we are all trying to get to.

Because the point of building an edge is not only to make money. It is to build a life.

The market closes. The children are waiting. The book can be reopened tomorrow.

Closing Thought

This ATOMIQ LEVEL conversation with James Bulltard is a rare look inside the mind of a trader who has built a business not by hiding the work, but by exposing it.

The story begins with a kid on Yahoo message boards, losing money and trying to understand why. It runs through the early technical lesson that made charts click.

It passes through the COVID-era explosion of online market personalities, where too many people were selling screenshots and confidence without accountability.

It becomes a Substack built on transparency. It becomes a Discord trading floor. It becomes a manually filtered options database. It becomes an AI-assisted rules engine. It becomes a community of professionals and serious traders looking for one more edge. But beneath all of that, the real story is trust.

Trust that the entries are real. Trust that the exits are shown. Trust that the book is open. Trust that the data is filtered. Trust that the person behind the avatar is not wasting your time.

For traders, this episode is a reminder that the market rewards discipline more than narrative. For investors, it is a reminder that even great companies have bad levels.

For advisors and family offices, it is a reminder that clients increasingly want access to transparent, specialized, high-signal independent voices.

For Substack writers, it is a reminder that conversion is not about audience size alone. It is about utility, trust, engagement, and proof.

And for anyone trying to understand the strange new world where one private avatar can outperform far larger finance brands, James Bulltard offers a simple lesson:

Show the work. Filter the noise. Respect the tape.

Press play on this episode with James Bulltard if you want to understand how a private trader turned options flow, moving averages, AI, transparency, and a brutally honest community into one of the most interesting finance businesses on Substack.

Because the market does not care how good your story sounds. It cares where the money is actually moving.

The real risk is doing nothing!

~Chris J Snook

Thank you to everyone who tuned into my live video! Join me for my next live video in the app.

Get more from Chris J Snook in the Substack app

Available for iOS and Android

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Wealth Matters TV Launches July 17, 2026, on Roku and Android TV,

Delivering Institutional-Grade Financial Education

to Mass-Affluent and High-Net-Worth Families Globally

New OTT Streaming Network Debuts with Original Broadcast Shows, Syndicated Substack Expert Podcasts, and Live Pay-Per-View Wealth Matters Weekend Retreats — with Additional Top Finance, Business & Tech Creator Signings Announced This Coming Fall.

LOS ANGELES, CA — June 9, 2026 —

Wealth Matters TV, the first streaming network built exclusively for families committed to building, protecting, and transferring wealth across generations, today officially launches on Roku and Android TV. The OTT network debuts as a free, ad-supported OTT channel with a premium (no-ad) and live pay-per-view summit tiers — bringing institutional-grade financial programming directly to the living rooms of millions of American households.

For decades, the most powerful wealth-building strategies — multigenerational estate planning, advanced tax optimization, family office architecture, and legacy investment frameworks — have been accessible only through private wealth management relationships and reserved for the ultra-wealthy. Wealth Matters TV was built to change that.

“Real wealth isn’t just a number. It’s net worth and net happiness — compounding, protected, and passed on for generations. Every family with the discipline to build wealth deserves access to the smart-money strategies that protect it. We built Wealth Matters TV so that the opportunity is open to everyone to help them find the way to secure their future, as complexity and challenges for retaining wealth compound daily.”
— Chris J. Snook, Founder, Wealth Matters Media | Bestselling Author, Wealth Matters 3.0 | Host, The ATOMIQ LEVEL Podcast

PROGRAMMING OVERVIEW

Wealth Matters TV’s initial programming slate spans four content pillars designed to serve mass-affluent and high-net-worth households at every stage of their financial journey:

• Original Broadcast Shows — Flagship series featuring leading registered investment advisors, estate planning attorneys, tax professionals, family office strategists, and generational wealth architects translating complex financial strategy into clear, actionable intelligence.

• Expert Financial Podcasts — Long-form, insight-driven conversations with practitioners on the front lines of wealth management, asset protection, and legacy planning.

• In-Depth Insider Interviews — Candid conversations with ultra-high-net-worth families, institutional investors, and financial innovators on the real mechanics of building multigenerational wealth.

• Live Semi-Annual Pay-Per-View Wealth Retreats — Premium live events connecting subscribers with the country’s top financial, legal, and estate planning minds for high-impact, one-day intensives on wealth protection, growth strategy, and legacy architecture.

CREATOR EXPANSION: FALL 2026 ANNOUNCEMENTS

Wealth Matters TV will announce a series of show signings and programming partnerships in Fall 2026, bringing some of the most respected voices in Finance, Business, and Technology from the Substack creator ecosystem onto the network. These forthcoming signings represent a significant expansion of the network’s programming slate and its mission to aggregate the most trusted independent voices in financial media under one premium destination for serious wealth builders.

Creators, authors, and podcast hosts interested in distribution, production partnerships, or co-development opportunities are invited to connect with the Wealth Matters Media team directly through the network’s streaming partner page.

WHO IT’S BUILT FOR

Wealth Matters TV is engineered for the 40 million American households with investable assets between $100,000 and $30 million — a segment historically underserved by both mainstream personal finance media and private wealth advisory services. Whether managing a $500K portfolio or a $50M family enterprise, every program on the network reflects one conviction: families who think in decades, not quarters, deserve programming that does the same.

NETWORK PHILOSOPHY

At the core of the Wealth Matters TV mission is the belief that financial security and personal fulfillment are not competing goals. The network’s programming is anchored in the Sovereign Wealth Architecture framework — the idea that true generational wealth integrates investment strategy, estate and tax planning, family governance, and personal values into a unified, multi-decade plan.

AVAILABILITY

Wealth Matters TV is now available free to all Roku and Android TV users. Premium live pay-per-view summits are available for individual purchase through the network platform. Broadcast, media, and brand partnership inquiries, as well as streaming distribution details, are available at wealthmatterstv.com.

Stream free. Attend live. Think generational.

ABOUT WEALTH MATTERS TV

Wealth Matters TV is an OTT streaming network distributed on Roku and Android TV, dedicated to giving mass-affluent and high-net-worth American families access to the investment, estate, tax, and legacy planning strategies that build and sustain generational wealth. The network offers free broadcast programming, expert financial podcasts, and live pay-per-view wealth summits, operating on the conviction that real wealth is both net worth and net happiness — compounding, protected, and passed on for generations.

ABOUT WEALTH MATTERS MEDIA

Wealth Matters Media is an omni-channel media company delivering research, newsletters, commentary, broadcast, and podcast content to mass-affluent and high-net-worth individuals and their advisors. Through its network of platforms and distribution channels, Wealth Matters Media connects serious wealth builders with the independent voices, expert insight, and actionable intelligence they need to protect and grow wealth across generations.

MEDIA, BOOKINGS & BRAND PARTNERSHIPS

For all media inquiries, booking requests, and brand partnership opportunities, please connect via the “Contact Us” button on the Wealth Matters TV streaming partners page.

Brand Partners Deck Request:

Substack Newsletter: wealthmatterstome.com

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About Chris J. Snook: Chris J. Snook is the Founder of Wealth Matters Media, a bestselling author, and Host of The ATOMIQ LEVEL Podcast. He is an investment strategist and generational wealth architect focused on making sovereign financial architecture accessible to every family committed to building lasting wealth.

# # #

Most articles focus on the money. Most families don’t.

Because if you’re a Gen Xer staring down this transition, the thing keeping you awake at night probably isn’t how much you’ll inherit.

It’s whether you’ll know what to do when the phone rings.

The truth is that most Gen Xers aren’t worried about inheriting wealth. They’re worried about inheriting more complexity and responsibility.

The Gen X Irony

Gen X may be the first generation in modern history that simultaneously worries about funding their children’s future, protecting their parents’ past, and preserving their own retirement.

They are expected to become the bridge between generations at precisely the moment many feel the least financially prepared themselves.

Researchers call GenX the Sandwich Generation. That label no longer feels sufficient. Many Gen X households are now supporting aging parents, helping adult children, managing careers, planning for retirement, and navigating their own cost-of-living increases, job insecurity, and health concerns simultaneously.

In many ways, Gen X has become the custodian and IT department of the family operating system. The problem is nobody ever handed them the user manual. This may explain why inheritance isn’t what most Gen Xers talk about when the conversation turns to aging parents.

The money is rarely the first concern. The responsibility is.

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The Inheritance Nobody Talks About

There is a running joke among Gen Xers that we were the “figure it out yourself” generation.

Hell, they were the kids who drank from garden hoses and didn’t wear helmets to ride bikes or ski, right? They came home when the streetlights turned on. They learned technology before our parents and before our children. They’ve spent most of their lives adapting. They were the original gamer generation, and now they’re about to battle one final boss.

The Family Operating System.

And unlike the VCR clock, nobody is leaving them the instruction manual.

The headlines call it the Great Wealth Transfer. However, for many Gen X adults, it feels more like the Great Responsibility Transfer.

Because what arrives first is rarely money. It’s decision-making. It’s caregiving. It’s coordination. It’s crisis management. It’s becoming the adult in the room while quietly wishing someone else could fill that role.

The Question Beneath Every Question

When families finally start discussing succession planning, the questions usually sound practical.

Do Mom and Dad have a will?

Is there a trust?

Who has power of attorney?

What accounts exist?

Who are the advisors?

Where are the passwords?

What happens if someone becomes incapacitated?

But underneath every one of those questions sits another. A much more important one.

Do we have clarity before a crisis forces us to find it?

Because when clarity is absent, conflict fills the vacuum. And conflict has a way of showing up at exactly the wrong moment.

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The Mess Gen X Actually Fears

What may surprise many people is that Gen X is one of the least inheritance-dependent generations in modern history. Most are not counting on an inheritance to fund their retirement.

Many have already assumed that healthcare costs, long-term care expenses, inflation, taxes, or simple longevity may consume a meaningful portion of whatever assets ultimately remain.

The fear is not the absence of assets. The fear is the absence of organization and understanding. The inheritance Gen X worries about isn’t a portfolio.

It’s a three-ring binder nobody can find. A trust nobody understands. A phone nobody can unlock. Accounts nobody knows exist. A safe deposit box with no key. A family disagreement nobody addressed. An aging parent whose memory has started to fade. A sibling conflict waiting to happen. The fear isn’t receiving too little. The fear is untangling too much.

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The Predators Are Already Circling

This is the part many families underestimate. The greatest threat to family wealth often isn’t market volatility. It’s vulnerability. The predators rarely arrive after death. They often arrive before it.

Financial scams.

Romance scams.

Identity theft.

Fraudulent caregivers.

Questionable contractors.

Manipulative acquaintances.

Aggressive salespeople.

Opportunistic relatives.

Bureaucratic systems that don’t care how overwhelmed a family may be. Many Gen X children quietly carry a fear they rarely articulate.

Will I spend the next decade protecting my parents instead of enjoying my remaining years with them?

That fear is real.

Because as parents age, protecting them often becomes less about investing and more about governance. Less about returns. More about oversight.

The Password/2FA Problem

Twenty years ago, estate planning was largely a legal exercise. Today, it is increasingly a technology and personal opsec (operational security) exercise.

Where is the will?

Now has company.

Where is the password manager?

Who has access to the phone?

Who controls the authenticator app?

Who can access email?

Who knows the recovery codes?

Who can access cloud storage?

What happens to cryptocurrency wallets?

What happens to subscription services, online accounts, and digital assets?

The modern estate is no longer just physical. It is digital. And for many families, the digital estate may create more friction than the financial estate.

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The Grief Nobody Talks About

There is another challenge that very few people discuss. Anticipatory grief. Anticipatory grief is the grief that begins before the actual loss.

Gen X is often watching this happen and experiencing it in real time. Their parents are slowing down. Their parents are forgetting things. Their parents are becoming less independent. Their parents, who once solved every problem, now need help solving their own more frequently.

At the exact moment, Gen X is being asked to become the family quarterback. It’s a strange emotional paradox. You don’t want the promotion. But eventually you realize you’re already doing the job.

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The Succession Burden Gap

There is a concept that deserves more attention.

The Succession Burden Gap.

For most of history, inheritance meant receiving assets. Today, inheritance increasingly means receiving administration.

The complexity surrounding family wealth is growing faster than the wealth itself. Assets. Liabilities. Insurance policies. Healthcare directives. Passwords. Subscriptions. Tax filings. Business interests. Family governance. Digital identities. Medical decisions.

The modern family balance sheet contains far more moving pieces than previous generations ever faced.

Inheritance is no longer simply a transfer of assets.

It is increasingly a transfer of responsibility.

And unless families intentionally transfer information before they transfer assets, the largest wealth transfer in history may also become the largest complexity transfer in history.

The Family Balance Sheet Nobody Tracks

Every family has two balance sheets.

The first contains assets and measures dollars.

The second contains trust and measures understanding.

Most families spend decades building the first. Very few intentionally build the second. Yet when a crisis arrives, the trust balance sheet often becomes the more valuable asset.

Do people know where things are?

Do expectations align?

Have difficult conversations occurred?

Does everyone understand the plan?

The strongest families are rarely the ones with the largest estates. They are the ones with the fewest unanswered questions.

A Better Way Forward

The good news is that most of these risks are solvable. Not with another financial product. Not with another investment, but with conversations.

Start simple.

Ask your parents:

What would happen if one of you became incapacitated?

Where are the important documents?

Who are your advisors?

What accounts exist?

What do you want us to know that we’ve never discussed?

What matters most to you if your health changes?

What are you worried about?

Then listen. Not as an heir. As a steward. Because the goal isn’t to figure out what you’re getting. The goal is to understand what you’re protecting and what chaos you are avoiding when you are also managing grief and loss.

Final Thought

The greatest wealth transfer in history may ultimately have less to do with money than information. The families that navigate the coming decades most successfully will not necessarily be the wealthiest, but they will be the clearest.

They will also be..

The ones who transferred knowledge before transferring assets.

The ones who documented the plan before the crisis.

The ones who replaced assumptions with conversations.

The ones who built both balance sheet assets and trust.

Succession is not ultimately about transferring wealth. It’s about transferring confidence. And confidence begins with clarity. Not after a loss. Before one.

You Are Not Alone:

Every Wednesday 1pm EST/10am PST Join ATOMIQ LEVEL AMA “Matt Chats” hosted by Chris J Snook

If this article struck a nerve, you’re not alone.

Every week, I hear from Gen X business owners, investors, professionals, and parents carrying these exact concerns.

That’s why I’m inviting you to join me and my longtime asset protection and estate planning counsel, Matt Meuli, for our free Wednesday ATOMIQ LEVEL “Matt Chats” Office Hours on Substack.

RESERVE YOUR SEAT FREE

We’ll go beyond theory and tackle the practical realities families face every day:

• How to start the conversation with aging parents.

• What documents matter the most.

• How to think about powers of attorney.

• The digital estate problem nobody is discussing.

• How to reduce future sibling conflict.

• How to protect aging parents from financial predators.

• How to organize family information before a crisis.

• How to build a family operating system that survives uncertainty.

Bring your questions. Bring your concerns. Bring your parents if they’re willing. Because the conversation you avoid today often becomes the crisis you inherit tomorrow.

The real risk is doing nothing.

~Chris J Snook

Sources & Research Summary

• Pew Research Center – The Sandwich Generation
  Research on adults simulta

  neously supporting aging parents and children, and the emotional and financial pressures involved.

• Northwestern Mutual Planning & Progress Study
  Findings showing many Americans expect to leave inheritances while far fewer expect to receive them.

• Trust & Will Estate Planning Report
  Estate planning preparedness by generation, including Gen X gaps in planning documents.

• Investopedia – Gen X Retirement and Family Support Trends
  Analysis of Gen X supporting multiple generations while trying to save for retirement.

• Kiplinger – Sandwich Generation Retirement Challenges
  Coverage of retirement savings sacrifices made by caregivers and multigenerational households.

• Morningstar – Gen X Retirement Anxiety Research
  Data on retirement readiness and financial stress among Gen X households.

• Elder Law Answers – Inheritance Expectation Gap
  Research showing a growing disconnect between what older generations intend to leave and what younger generations expect to receive.

• MarketWatch – Caregiving and Estate Planning Conversations
  Guidance and research on family communication, caregiving, and planning before a health crisis.

• World Quality Corporation – Costs of Supporting Aging Parents
  Discussion of healthcare, caregiving, and long-term care financial realities facing Gen X families.

• Choice Mutual – Great Wealth Transfer Estimates
  Summary and aggregation of major forecasts estimating the scale of the coming intergenerational wealth transfer.

Last week’s Matt Chats episode

Artificial Intelligence + Actionable Intelligence = Actual Intelligence

Actual Intelligence + Trust = Appreciating Assets

Every Token Ultimately Rests on Atoms.

Every Economy Ultimately Rests on Trust.

Every Future Ultimately Rests on Human Agency.

Section I: From Tokens to Trust

Why You Should Read/Listen to the Full Piece

If you’re anything like me, you’ve probably spent the last two years experiencing a strange combination of excitement and unease.

Every day seems to bring another headline announcing a breakthrough in artificial intelligence. Entire industries are being told they will be transformed. Investors are pouring hundreds of billions of dollars into infrastructure. Governments are racing to secure semiconductor supply chains. Data centers are appearing across the landscape. Every company suddenly claims to be an AI company. Every startup deck seems to include the letters AI somewhere on the first page.

Meanwhile, ordinary people are left wondering what any of it actually means.

What does it mean for your job?

What does it mean for your children?

What does it mean for your business?

What does it mean for your retirement?

What does it mean for your portfolio?

What does it mean for the country?

And perhaps most importantly, how do you separate signal from noise in a world where everyone seems certain about a future nobody can actually predict?

I have found myself asking many of those same questions.

Not because I fear technology. Quite the opposite. My career has largely been built around studying technological disruption and helping organizations navigate periods of rapid change. But experience has taught me that the biggest risks rarely come from the technology itself. They come from misunderstanding the system surrounding the technology.

We often become so fascinated by the invention that we fail to notice the incentives, assets, institutions, infrastructure, and human behaviors that determine whether the invention ultimately creates prosperity or destroys it. After recent interviews I did with and I dove deeper into my own frameworks and reconsidered what it means to my readers and me in a parallel sense-making synthesis of the implications.

That is why I believe the most important question surrounding artificial intelligence is not how smart the machines become.

The most important questions are how we measure the impact they (bits) have and how we invest in their insatiable appetite for physical resources (atoms).

Because if we are using the wrong scoreboard, we may be optimizing for outcomes that ultimately make us weaker rather than stronger.

And that realization has led me down a path that connects artificial intelligence, token economies, energy infrastructure, human agency, trust, national wealth, and one deceptively simple question:

If GDP is no longer the right scoreboard, what is?

The Chart That Made Me Stop

A few weeks ago, I was reviewing a collection of technology adoption metrics when I came across a chart tracking software development activity on GitHub.

The curve looked almost absurd as 2026 was on pace to achieve 14B (not in the historical chart below).

GitHub COO Kyle Daigle noted that GitHub activity had accelerated to roughly 275 million commits per week in early 2026, highlighting how rapidly AI-assisted software development is expanding. Author Note: If this current pace continues it would almost triple the volume of 2025 by end of this year. Source

Commits, repositories, contributions, and developer activity were all accelerating. At first glance, it looked like another technology chart. We’ve all become numb to exponential curves.

But the longer I looked at it, the more interesting it became. Because the chart wasn’t really measuring software. It was measuring something deeper.

It was measuring the conversion of intelligence into action. Every commit represents an idea transformed into a system. Every deployment represents knowledge becoming utility. Every repository represents accumulated problem-solving capacity.

In many ways, GitHub has become one of the world’s largest living records of human and increasingly artificial intelligence being translated into executable action.

That distinction matters.

For most of human history, intelligence was scarce. Every calculation originated in a human brain. Every design originated in a human brain. Every innovation originated in a human brain.

Today, we are entering a world where intelligence itself is becoming abundant. That abundance changes everything.

And it led me to a simple equation that has increasingly become the lens through which I view the next decade.

The Three AI’s

1) Artificial Intelligence + 2) Actionable Intelligence

= 3) Actual Intelligence

At first glance, it sounds like wordplay. It isn’t. The rest of this piece will attempt to prove this thesis to you as I have done to myself thus far.

In fact, I believe that simple equation above may be one of the most important economic equations of the coming decade.

Artificial intelligence by itself is merely potential.

It is capability. It is possibility. It is latent power waiting to be directed.

Actionable intelligence is something different. Actionable intelligence is intelligence guided by purpose and put to purpose.

It is intelligence directed toward an outcome. It is where judgment enters the system. It is where trust enters the system. It is where human agency enters the system.

And when artificial intelligence is combined with actionable intelligence, something entirely different emerges.

Actual intelligence.

Actual intelligence is intelligence that produces desired outcomes.

Not possibilities. Not predictions. Not simulations.

Outcomes.

This distinction will become increasingly important as we move deeper into the Intelligence Economy. Because abundance changes what is scarce. And scarcity determines value.

My Front Row Seat to the Token Economy

Long before artificial intelligence became the dominant topic of conversation, I found myself captivated by another question 15 years ago.

What happens when value becomes programmable?

That question eventually led me into one of the most fascinating periods of my professional life.

Between 2017 and 2020, I had the opportunity to help convene some of the earliest global conversations surrounding tokenization, digital ownership, incentive design, and emerging economic systems through the World Tokenomic Forum.

What started as a side project fueled by a kitchen table conversation with my co-author in Grand Cayman following a book signing event in October 2017, evolved into something much larger.

The conversations took us from Grand Cayman to Vilnius, Lithuania. From Hong Kong to Laramie, Wyoming, between 2017-2021 despite Covid’s plans thwarting much more in the 2020-2021 period.

Along the way, I met entrepreneurs, regulators, economists, software architects, investors, futurists, policymakers, and academics, all wrestling with a similar challenge.

How do you create systems that coordinate value in a digital world while the majority of value still transacts in an analog legal precedent?

At the time, most people viewed tokens through a very narrow lens. They saw cryptocurrency. Speculation. Price charts. Volatility. Scam after scam, etc.

Those things certainly existed. But they were never the most interesting part of the story to me. The deeper thinkers understood that tokens were not really about cryptocurrency. Tokens were real. Tokens were containers. Tokens were about coordination. Token economies were about incentives. Tokens were about ownership. Tokens were about trust. Tokens were about utility. And these tokens were now fully programmable.

Looking back now, many of those conversations feel less like predictions and more like early reconnaissance missions into a future that is arriving slower than the early minority expected, but suddenly for the rest of society.

One of the most influential thinkers I encountered during that journey was , co-author of Trillions.

Years before AI became a household topic, Mickey and his co-authors were exploring what happens when computation becomes pervasive and the impacts it has on the “built” world of atoms.

Their central insight was profound. As compute becomes embedded everywhere, intelligence becomes ambient.

We stop interacting with computers. We begin living inside computational environments. At the time, that sounded futuristic.

Today it feels increasingly obvious.

Large language models, autonomous agents, ubiquitous sensors, and AI-enhanced systems suggest we are rapidly moving toward a world where intelligence itself becomes part of the infrastructure layer of society.

Looking back, those conversations were not merely about technology. They were about economics. They were about incentives. They were about trust. And ultimately, they were about human behavior.

What Most People Get Wrong About Tokens

One of the biggest misunderstandings today is the word “token” itself. People hear the term and immediately think of cryptocurrencies. Bitcoin. Ethereum. Memecoins. Stablecoins. Speculative assets.

That association is understandable. But it is also limiting. Because tokens existed long before blockchains. In fact, most of us used tokens as children.

Remember arcade tokens?

You walked into the arcade carrying dollars. Those dollars worked almost everywhere. Inside the arcade, however, you exchanged those dollars for tokens. Those tokens had no inherent value outside of those four walls.

Their value came from what they unlocked.

Pac-Man.

Donkey Kong.

Galaga.

The token was simply a container. The utility lived inside of it.

The same thing happened at laundromats. You exchanged quarters for specialized tokens. Those tokens unlocked washing machines. They unlocked drying machines. Again, the token itself wasn’t the value. The token was simply the container that represented access to value.

Once you understand this distinction, the entire digital economy begins to look different. Airline miles are tokens. Hotel points are tokens. Gift cards are tokens. Property deeds are tokens. Stock certificates are tokens. Driver’s and hunting/fishing licenses are tokens. Membership cards and subscriptions are tokens.

Money itself is arguably a token representing a claim on economic value, or in the case of the last 55 years (since 1971), a pure fiat piece of paper with George Washington’s face on it, that is merely a tokenized unit of the national debt, in circulation, owed to the Federal Reserve Bank, functioning as official legal tender to settle your transactions in the USD hegemonic global economy.

The digital economy allows us to create, transfer, program, and coordinate these containers at unprecedented scale and speed. The hyper-emergent token economy is not replacing the physical economy.

It is creating a second operating system on top of it.

Atoms remain below.

Bits that operate above.

Tokens become the containers through which value moves between these two layers at light speed 24/7/365.

This realization eventually led me to another conclusion that I believe is becoming increasingly important.

Every token ultimately rests on atoms, which are still governed by the laws of physics. And every economy ultimately rests on both physics and the existence of trust between counterparties.

That realization became the bridge to a much bigger question.

If intelligence is becoming abundant, and tokens are increasingly becoming the containers through which value moves, what assets become more valuable rather than less valuable?

To answer that question, we need to leave the digital world for a moment and return to the physical one in Section II.

Because despite all the excitement surrounding artificial intelligence, the future remains firmly anchored in something surprisingly old-fashioned.

Atoms.

Before you enjoy the remaining two sections for “free” I have 4 simple requests if you have gotten value from this thus far.

1. Share this post and publication with your network and friends.

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2. Leave a comment/Join the conversation and bring it to life.

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Section II: The Great Inversion

More than a century ago, Henry Ford famously observed:

“Thinking is the hardest work there is, which is probably the reason so few engage in it.”

At the time, the statement reflected the realities of the industrial economy. Physical labor was abundant. Machines were becoming increasingly capable. Factories were scaling production. Yet genuine thinking—the ability to reason, solve problems, make decisions, imagine alternatives, and allocate resources—remained scarce.

Thinking was hard because it was limited to human beings, who were also limited by their access to knowledge and literacy at scale. Every innovation required a human mind. Every strategy required a human mind.

Every design required a human mind. Every meaningful decision required a human mind. For most of modern economic history, thinking was among the scarcest resources available to civilization.

Fast forward more than one hundred years to today, and NVIDIA CEO Jensen Huang recently offered an observation that sounds remarkably similar, yet comes from the exact opposite direction.

Discussing artificial intelligence infrastructure, Huang noted that:

“Inference (machine thinking) is the most expensive workload.”

As wrote this week, this was the thing about the AI boom that all of the smart money got wrong in the early wave of capital allocation when they thought that “training” was the more expensive “input”.

For those unfamiliar with the terminology, inference is the process of an AI system actually “thinking” through a problem and generating an answer.

Training teaches the model. Inference puts that training to work.

Training creates capability. Inference creates utility.

Training is potential. Inference is action. And action is expensive.

The more I reflected on the juxtaposition of Ford’s legendary observation and Huang’s visionary one, the more I realized they may collectively describe one of the most important economic transitions in human history.

Ford was describing a world where thinking was the hardest work humans could do.

Huang is describing a world where thinking is becoming the most expensive work machines can do.

Read that again.

For over a century, human beings were the primary producers of intelligence. Today, we are building systems capable of producing intelligence at scale.

That shift changes everything.

Not because machines are replacing humans. But because intelligence itself is transitioning from scarcity toward abundance.

And whenever something abundant replaces something scarce, the entire value structure surrounding it begins to change.

The Age of Abundant Intelligence

For most of the industrial era, economic systems were organized around scarce intelligence and relatively abundant physical resources.

The challenge was finding enough skilled people to transform raw materials into productive output.

Capital flowed toward labor. Labor transformed resources. Resources became products. Products generated economic activity. GDP became the scoreboard.

That framework made sense because intelligence was constrained by population. There were only so many engineers. Only so many scientists. Only so many analysts. Only so many entrepreneurs.

Only so many people were capable of solving difficult problems. Artificial intelligence changes that equation.

For the first time in history, we are creating systems capable of generating analysis, recommendations, software, designs, simulations, forecasts, and increasingly complex decisions at a scale unimaginable even a decade ago.

The implications are profound. Intelligence is no longer constrained solely by population growth. It is increasingly constrained by infrastructure.

That distinction may prove to be one of the most important investment insights of the next decade. Because as intelligence becomes abundant, something else becomes scarce.

And scarcity is where value accumulates asymmetrically.

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Why Atoms Still Matter

This is where many futurists and tech bros lose the plot, in my humble opinion. The popular narrative suggests that artificial intelligence somehow liberates us from the physical world.

The opposite may be true. Artificial intelligence is not replacing atoms, it is consuming them.

Every AI prompt requires electricity. Every inference requires compute. Every compute cycle requires semiconductors. Every semiconductor requires fabrication facilities. Every fabrication facility requires land, water, chemicals, energy, and specialized materials. Every data center requires copper. Every transformer requires copper. Every transmission line requires copper. Every cooling system requires water. Every backup system requires fuel. Every server rack requires steel, aluminum, concrete, and real estate.

The cloud is not floating in the sky. The cloud is sitting on a human’s, company’s, or nation’s balance sheet. And that balance sheet is made of atoms.

One of the biggest misconceptions of the AI era is the assumption that digital abundance somehow eliminates physical scarcity.

It does not.

In many ways, it amplifies it. Every token eventually touches an atom. Every bit ultimately rests upon infrastructure. Every intelligence transaction consumes physical resources somewhere. The intelligence economy is not escaping the laws of physics. It is becoming increasingly dependent upon them.

As investors, we should pay close attention whenever a technological revolution increases demand for foundational resources and capital.

History repeatedly shows that the greatest fortunes are often built not only by the companies creating the new technology, but also by those controlling the infrastructure beneath it.

1. The railroads enriched rail operators, but also steel producers, coal suppliers, equipment manufacturers, and landowners.

2. The automobile revolution enriched car companies, but also energy producers, road builders, insurers, and logistics networks.

3. The internet enriched software companies, but also fiber providers, semiconductor manufacturers, and network infrastructure operators.

4. Artificial intelligence appears poised to follow the same pattern.

The Great Inversion

This realization led me to what I now call The Great Inversion.

Historically, intelligence was scarce, and physical resources were abundant. Today, intelligence is becoming abundant while the assets required to support intelligence are becoming increasingly strategic.

The more intelligence we create, the more energy we consume. The more agents we deploy, the more compute we require. The more automation we build, the more infrastructure we need. The more digital value we create, the more physical systems must support it.

This inversion changes how we think about value creation. The future will not be won solely by those who create intelligence. The future may belong to those who own the assets intelligence requires to operate.

Energy.

Copper.

Water.

Land.

Compute infrastructure.

Semiconductor manufacturing.

Transmission capacity.

Data centers.

And perhaps most importantly, trust.

This is the inversion that too few people are discussing. As intelligence becomes abundant, the physical and institutional assets supporting intelligence become increasingly valuable.

The more valuable intelligence becomes, the more valuable its dependencies become. The more valuable its dependencies become, the more important balance sheets become.

Which brings us directly to the problem with GDP.

The Scoreboard We Inherited

Gross Domestic Product is one of the most influential economic measurements ever created.

For decades, it has served as the primary scorecard used by governments, economists, investors, and policymakers to evaluate economic performance.

GDP measures activity. (How much was produced? How much was consumed? How much was spent? How much changed hands?)

It was an extraordinary innovation for the industrial era because industrial economies were largely organized around production.

Factories produced goods. Workers produced output. Consumers purchased products. Governments measured the resulting economic activity.

The framework worked because most value creation was visible and tangible.

You could count automobiles. You could count homes. You could count factories. You could count steel production. You could count economic output.

But as economies become increasingly digital, automated, tokenized, and intelligent, GDP begins to reveal its limitations. Imagine an AI system that enables a company to accomplish in one hour what previously required ten employees working all week.

Has value been created? Almost certainly.

Has productivity increased? Absolutely.

Has the total capability improved? Without question.

Will GDP necessarily capture all of that value? Not always.

In some cases, GDP could actually appear weaker because fewer labor hours, fewer transactions, or lower operating costs are involved.

The measurement system begins to struggle because the nature of value creation itself is changing. This doesn’t make GDP wrong.

It simply makes GDP incomplete.

And incomplete scoreboards often produce incomplete decisions.

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Roger Ohan and the GDP Problem

One of last week’s most thought-provoking conversations that I have had was with Roger Ohan on the ATOMIQ LEVEL (see the “Sources” section for the link). Roger introduced his GNA framework that immediately resonated with me because it addressed something I had been wrestling with for years.

GDP measures activity. But activity is not wealth. Activity is not resilience. Activity is not optionality. Activity is not strategic strength.

Activity is a flow. Wealth is a stock.

Those are fundamentally different concepts.

Imagine two nations.

Nation A generates extraordinary GDP growth through borrowing, consumption, and short-term economic activity.

Nation B grows more slowly but steadily accumulates energy assets, infrastructure, intellectual property, educational advantages, water security, technological capabilities, and strategic resources.

Under traditional GDP analysis, Nation A may appear stronger.

But under a balance sheet framework, Nation B may actually be building a more durable foundation for future prosperity.

This distinction becomes increasingly important as intelligence becomes an economic asset. Artificial intelligence is not merely another technology.

It is a force multiplier.

And force multipliers amplify whatever foundation exists beneath them. A nation with abundant energy, strong institutions, trusted markets, educated citizens, robust infrastructure, and strategic resources may experience enormous gains from AI adoption.

A nation lacking those foundations may discover that intelligence alone is insufficient.

Because intelligence is not self-sustaining. Intelligence must be fed. And what feeds intelligence increasingly looks like a balance sheet problem rather than a GDP problem.

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The Five Capitals of the Intelligence Age

As I continued exploring these ideas through conversations with investors, economists, entrepreneurs, technologists, and policymakers, I found myself searching for a framework capable of capturing the broader picture.

The result is still evolving, but increasingly, I believe the Intelligence Economy can be understood through five interconnected forms of capital.

Natural Capital: includes energy resources, water systems, minerals, agricultural capacity, ecosystems, and land. Every economic system ultimately rests upon the natural world. These assets often sit quietly beneath daily life, yet they remain foundational to everything else. (I suggest you read and follow on Substack and listen to the ATOMIQ LEVEL interview we did months back for more on his emergent natural capital asset class framework)

Infrastructure Capital: includes power grids, data centers, fiber networks, transportation systems, logistics networks, ports, communications systems, and semiconductor manufacturing capacity. Infrastructure determines how effectively resources can be transformed into productive activity.

Financial Capital: includes savings, credit systems, equity markets, debt markets, reserves, liquidity, and capital allocation mechanisms. Financial capital determines how efficiently opportunities can be funded and risks can be absorbed.

Intelligence Capital: includes human expertise, research institutions, intellectual property, software, data assets, artificial intelligence systems, and accumulated knowledge. Intelligence capital increasingly drives competitive advantage.

The fifth and perhaps most underappreciated is Agency Capital.

Agency Capital consists of trust, governance, reputation, property rights, institutional legitimacy, rule of law, social cohesion, and human decision-making capacity.

Agency Capital determines whether societies can coordinate effectively. It determines whether individuals trust institutions. It determines whether capital can be deployed confidently. It determines whether intelligence can be converted into action.

And that is where our equation reconnects.

Artificial Intelligence + Actionable Intelligence = Actual Intelligence.

Actionable intelligence is where Agency Capital enters the system.

Human judgment. Human values. Human accountability. Human purpose.

These are not side effects. They are prerequisites. Because intelligence without direction is merely noisy chaos. Only when intelligence is combined with agency does it become capable of producing meaningful outcomes. And only when meaningful outcomes are trusted do they become durable sources of wealth. This is why you should also tune into the ATOMIQ LEVEL conversation in the “Sources” that I had with , on the role human agency must play in this unfolding future if we are to get it “right”.

This realization may ultimately be the bridge between Roger Ohan’s Gross National Assets framework and the future of artificial intelligence, and the roadmap to both value creation within your portfolio and the net happiness quotient that is unique to the human experience we all crave to see persist.

The economies that win the next decade may not be the ones generating the most activity. They may be the ones most effectively compounding all five forms of capital simultaneously.

Which raises perhaps the most important question of all.

In a world where intelligence is becoming abundant, what remains uniquely human?

Section III: The Human Agency Premium

You are still here! Bless you for sticking with this piece, or for coming back to it after some needed mental digestives.

If Section I was about understanding the emergence of the token economy, and Section II was about understanding why the physical world matters more than many people realize, then this final section is ultimately about understanding the one asset that may become more valuable than all the others combined.

The human being.

That statement may sound strange inside an article focused on artificial intelligence. Yet the deeper I have gone down this rabbit hole over the past decade, the more convinced I have become that the future is not primarily a story about machines.

Like all great moments across history. It is a story about people.

More specifically, it is a story about what happens when billions of humans suddenly find themselves surrounded by trillions of digital entities capable of producing intelligence, coordinating action, making recommendations, conducting transactions, and interacting with one another at speeds and scales never before witnessed. What McManus et al profoundly described as “thriving in the emerging information ecology.”

Because that is the future that is emerging. And I believe most people are dramatically underestimating how different that world may look.

The Population Explosion Nobody Is Talking About

When economists discuss population growth, they typically focus on humans.

Birth rates. Demographics. Immigration. Labor participation. Dependency ratios. These metrics have mattered because, for most of history, every productive unit of intelligence originated from a human being.

A company with one hundred employees effectively had one hundred units of productive intelligence.

A nation with one hundred million citizens had one hundred million sources of intelligence. The size of the population largely determined the upper limits of economic output.

Artificial intelligence changes that relationship. Over the next decade, it is entirely possible that every individual will be supported by dozens, hundreds, or even thousands of specialized AI agents operating on their behalf. Some will negotiate. Some will research. Some will transact. Some will write. Some will analyze. Some will monitor. Some will coordinate. Some will educate. Some will sell. Some will buy. Many will communicate directly with other agents.

The result is that the population of non-human intelligence may soon exceed the population of biological intelligence by orders of magnitude.

Humanity may be entering the first era in history where intelligence itself is no longer constrained by the number of people alive.

That reality has profound implications.

Because whenever something becomes abundant, something else becomes scarce. And scarcity determines value.

The Scarcity Shift

For centuries, intelligence was scarce. Today, intelligence is becoming abundant. The question investors should be asking is simple:

What becomes scarce next?

The answer, I believe, is human agency. This is where my conversation with Michael Casey, mentioned earlier, became particularly illuminating.

Michael has spent years exploring the intersection of technology, decentralized systems, economics, governance, and human freedom. Throughout our discussion, one theme repeatedly surfaced.

The future is not fundamentally a contest between humans and machines. The future is a contest over agency.

Who decides?

Who directs?

Who authorizes?

Who is accountable?

Who determines the objective?

Who determines what success looks like?

These questions become more important as intelligence becomes easier to produce. Because intelligence alone does not determine outcomes. Direction determines outcomes. Purpose determines outcomes. Values determine outcomes. Agency determines outcomes.

And agency remains profoundly human. At least for now.

The irony of the Intelligence Economy is that as intelligence becomes abundant, judgment becomes scarce. As answers become abundant, wisdom becomes scarce.

As automation becomes abundant, responsibility becomes scarce. As agents become abundant, purpose becomes scarce. This is why I increasingly believe that human agency may become one of the most valuable assets on Earth.

Not because humans are smarter than machines. But because humans remain the source of purpose. For now and the foreseeable future.

Why Actionable Intelligence Matters

This is precisely why I have become increasingly attached to the equation introduced earlier in this article.

Artificial Intelligence + Actionable Intelligence = Actual Intelligence

The reason this equation matters is because the majority of recent or mainstreeam AI discussions stop at artificial intelligence. They assume intelligence itself is the destination.

It isn’t.

Artificial intelligence creates possibilities. Actionable intelligence determines which possibilities deserve action. Actual intelligence creates outcomes.

That middle layer is where human beings continue to play an indispensable role. Actionable intelligence is not simply information. It is judgment. It is context. It is prioritization. It is values. It is deciding what matters. It is deciding what doesn’t.

It is determining what future is worth pursuing. In practical terms, actionable intelligence is where human agency enters the system. Without agency, artificial intelligence remains potential.

With agency, artificial intelligence becomes productive. Without agency, intelligence generates options. With agency, intelligence generates outcomes.

The winners of the next decade may not be those who possess the most artificial intelligence. They may be those who most effectively combine artificial intelligence with human judgment.

Digital Sense and the Human Experience

This conclusion brings me full circle over the past decade and back to the book I co-authored with .

When Digital Sense was published by Wiley in 2017, artificial intelligence was nowhere near the center of public conversation that it occupies today.

Yet one of the central themes of the book feels even more relevant now than it did then.

Technology changes. Human nature does not. Platforms change. Human psychology does not. Tools evolve. Human motivations remain remarkably consistent.

One of the observations we explored throughout the book was that as products become commoditized and information becomes ubiquitous, customer experience increasingly becomes the primary differentiator that drives the premium a brand can demand in the marketplace.

Companies can copy features. They can copy pricing. They can copy functionality.

What becomes increasingly difficult to copy is the relationship a brand establishes with its customers. At the time, we were writing about digital transformation, social media, customer engagement, and emerging technologies.

What we did not fully appreciate was how relevant those ideas would become in the Intelligence Economy. Because, the rise of artificial intelligence does not eliminate the importance of customer experience. It amplifies it.

The Human Customer and the Agentic Customer

And more than that, it now requires design thinking around the parallel Agentic customer journey as well as the human customer journey. For the first time in history, businesses find themselves serving two distinct customer populations simultaneously.

Human customers. And agentic customers.

The human customer wants empathy, reliability, simplicity, and expects speed, less friction, and personalization.

The human customer wants confidence and value for their money. The human customer wants understanding. The human customer wants reassurance. The human customer wants to feel seen and heard. The human customer wants trust.

However, The agentic customer wants something entirely different.

The agentic customer wants access. The agentic customer wants APIs. The agentic customer wants permissions. The agentic customer wants machine-readable information. The agentic customer wants efficiency. The agentic customer wants outcomes.

Today, nearly every company is designed around the human customer experience, and has barely caught up to the implementation of that in their digital transformation efforts across the silos.

Tomorrow’s companies will need to design for both. This creates a fascinating challenge and a massive “leap-frog” opportunity, because agentic customers will likely outnumber human customers by an order of magnitude in the coming decade. Every individual may have dozens, hundreds, or even thousands of agents acting on their behalf. Examples include:

Agents researching investments.

Agents evaluating healthcare providers.

Agents comparing insurance products.

Agents booking travel.

Agents negotiating contracts.

Agents managing subscriptions.

Agents purchasing products.

Agents coordinating workflows.

Many transactions that currently occur between humans may increasingly occur between agents. Customer experience itself is about to bifurcate. There will be a Human Customer Experience. And there will be an Agentic Customer Experience.

The companies that thrive will likely excel at both. They will build systems that allow agents to transact efficiently while simultaneously preserving the human trust that makes those transactions meaningful. This is not an either-or proposition.

It is a both-and proposition.

Because while agentic customers may become numerically dominant, human customers remain economically and emotionally supreme.

1. The agent may execute the transaction. The human still owns the objective.

2. The agent may compare the products. The human still assigns the value.

3. The agent may negotiate the price. The human still determines what matters.

This distinction becomes critically important because many organizations may become tempted to optimize exclusively for the machine.

History suggests that would be a mistake.

The greatest brands of the next decade may not be those that build the most efficient agent interfaces. They may be those who best understand the human being sitting behind those agents.

The empathy map does not disappear. It becomes more valuable.

The relationship does not disappear. It becomes the scarcest asset.

The trust equation does not disappear. It becomes more important.

Because even in an economy increasingly populated by artificial agents, the final measure of success remains deeply human. Someone still has to care. Someone still has to trust. Someone still has to choose. And that someone is still a person.

The Trust Layer

There is another scarce resource emerging alongside agency.

Trust.

In many ways, trust may become the most valuable economic asset of the Intelligence Age.

The reason is simple:

When information becomes abundant, verification becomes scarce.

When content becomes abundant, credibility becomes scarce.

When intelligence becomes abundant, trust becomes scarce.

The internet dramatically increased the amount of information available to humanity. Artificial intelligence is dramatically increasing the amount of intelligence available to humanity. Both developments create extraordinary opportunities. Both developments also create extraordinary noise.

The challenge is no longer obtaining information. The challenge is determining which information deserves confidence.

The challenge is no longer obtaining intelligence. The challenge is determining which intelligence deserves action.

Trust becomes the filter. Trust becomes the coordination mechanism.

Trust becomes the infrastructure. Trust becomes the bridge between intelligence and action.

What makes this challenge even more important is that we are entering the Intelligence Age at a moment when trust is already under extraordinary pressure.

The 2025 Edelman Trust Barometer described the current environment as a global “Crisis of Grievance,” finding that economic fears have evolved into widespread distrust of institutions, leadership, and information itself. Roughly six in ten respondents across 28 countries reported moderate-to-high levels of grievance, driven by a belief that government, business, and other institutions increasingly serve narrow interests while ordinary people struggle. Perhaps most troubling, seven in ten respondents believe leaders regularly mislead the public through exaggeration or falsehoods.

Think about what that means in the context of artificial intelligence.

If trust is already fragile in a world dominated by human-generated information, what happens when the volume of machine-generated content, analysis, recommendations, and synthetic media expands by orders of magnitude?

The challenge is no longer finding answers. The challenge is knowing which answers deserve trust. THAT IS WHY WE SUBSTACK. This is why I put my energy into thr long form conversation here. This is why your comments matter to EVERY discussion!

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The challenge is no longer accessing intelligence. The challenge is determining which intelligence deserves action. This realization has profound implications for investors, businesses, institutions, and families.

Because trust compounds. Just like capital compounds.

In fact, trust may prove to be the highest-return asset on the balance sheet of the Intelligence Economy. The organizations that consistently earn trust will attract attention.

Attention will attract relationships. Relationships will attract opportunities. Opportunities will attract capital. And capital, when deployed intelligently, compounds.

This is one reason the Edelman research continues to find that people place more trust in their direct employer than in virtually any other major institution. In an era defined by uncertainty, people increasingly anchor themselves to relationships and organizations that demonstrate competence, transparency, and accountability.

In a world increasingly filled with synthetic intelligence, trusted human relationships may become even more valuable than they are today.

Not less. More.

Because trust is what transforms information into belief. Belief into action. And action into lasting value.

Actual Intelligence Plus Trust

As I continued connecting these dots, another equation emerged.

Actual Intelligence + Trust = Appreciating Assets.

This may be the most important equation in the entire article. Because intelligence alone does not create wealth. Execution alone does not create wealth. Technology alone does not create wealth.

What creates wealth is the consistent conversion of intelligence into trusted outcomes.

Trusted outcomes create confidence. Confidence attracts capital. Capital funds innovation. Innovation creates productivity. Productivity creates wealth. Wealth creates optionality. Optionality creates resilience. And resilience creates the capacity to endure uncertainty. That entire cycle depends upon trust. Without trust, the system breaks down. Without trust, transactions become more expensive. Without trust, coordination becomes more difficult. Without trust, intelligence loses value.

The economies that understand this principle may gain a significant advantage in the years ahead.

The Race to Own the Future

This brings us back to ‘s framework and the concept of Gross National Assets, and all of the recent complementary analysis by the unbelievably prolific mind of in his last 4 posts.

If GDP measures activity, then GNA attempts to measure capacity.

GDP asks: How much happened?

GNA asks: What do we own?

GDP asks: What was produced?

GNA asks: What can be produced tomorrow?

GDP measures flows. GNA measures foundations.

The distinction becomes increasingly important as artificial intelligence reshapes the global economy. Because the future may not belong to the countries generating the most activity. The future may belong to the countries accumulating the strongest asset base. Energy. Infrastructure. Natural resources. Human capital. Intelligence capital. Trust capital. Agency capital.

The Five Capitals framework is ultimately an attempt to measure these foundations. And what is true for nations is equally true for businesses, families, and individuals.

The question is not simply how much income you generate. The question is what assets you are accumulating.

The question is not simply how much activity you create. The question is whether your capabilities are compounding.

The question is not simply whether you are adopting AI. The question is whether AI is helping strengthen your balance sheet.

Because artificial intelligence can amplify strengths. It can also amplify weaknesses.

And force multipliers are unforgiving.

Why Wealth Matters 3.0 Exists

As I look back on the journey from co-authoring Digital Sense in 2017, to helping organize the World Tokenomic Forum, to hosting hundreds of conversations through ATOMIQ LEVEL and Wealth Matters 3.0, one conclusion continues to crystallize.

The future belongs neither to the technologists nor the traditionalists. It belongs to the translators, and what I lovingly coined the “sense-makers” when we published Digital Sense.

Sensemakers are:

The people capable of helping others navigate complexity.

The people willing to challenge assumptions.

The people willing to remain intellectually curious.

The people willing to continuously learn.

The ATOMIQ LEVEL conversations I’ve been fortunate to have with Roger Ohan, Charlie Garcia, Michael Casey, Mickey McManus, Michael Howell, Brent Johnson, and many others are not about finding certainty. They are about building better frameworks for navigating uncertainty and shortening the learning curve while reducing the cost of each failure or necessary learning.

That is why Wealth Matters 3.0 exists. That is why ATOMIQ LEVEL exists. That is why our premium subscriber weekly office hours with ’s “Matt Chats” on asset protection and estate/succession planning exist.

Not because anyone has all the answers. But, because better questions lead to better decisions. And better decisions compound.

The free and paid members of the Wealth CMDR community are not subscribers. You and they are my fellow explorers. My fellow builders. My fellow translators. And the lifeblood of this work that gives me meaning. Thank you for reading.

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The real risk is doing nothing

~Chris J Snook

Sources & Further Exploration

The ideas explored in this article are drawn from a combination of public research, books I’ve read or written, reports, previous interviews I’ve done, and personal observations accumulated over nearly 15 years studying digital transformation, tokenization, artificial intelligence, economics, and capital markets.

While this article reflects my own synthesis and conclusions, I encourage readers to explore the original source materials below and form your own perspective and thesis.

Related Posts From my own Subscriptions I Respect/Rely On:

Capital Mischief

The Machines Are Writing the World's Code Now. Almost Nobody Can Explain How.

Read more

10 days ago · 343 likes · 118 comments · Charlie Garcia

Wealth Matters 3.0 & ATOMIQ LEVEL Conversations

Roger Ohan — Gross National Assets (GNA) Framework

ATOMIQ LEVEL Interview

A foundational conversation exploring why Gross National Assets (GNA) may become a more useful framework than GDP for understanding national wealth creation, productive capacity, and long-term economic resilience in the Intelligence Economy.

Michael Casey — Human Agency and the Intelligence Economy

ATOMIQ LEVEL Interview

An exploration of human agency, decentralized systems, artificial intelligence, governance, trust, and the role of human decision-making in an increasingly automated world.

Matt Ross — Natural Capital in an Artificial Economy

ATOMIQ LEVEL Interview

David Johnston — Owning Your Inference vs Renting it Back For Life is the 100x Gap

ATOMIQ LEVEL Interview

Book’s Referenced:

Digital Sense

Chris J. Snook & Travis Wright (Wiley, 2017)

https://www.amazon.com/Digital-Sense-Transform-Experiences-Connect/dp/111936225X

Explores how digital transformation, customer experience, emerging technologies, and evolving consumer expectations reshape competitive advantage. Many of the ideas around trust, experience, and relationship-building discussed in this article were first explored here.

Trillions

Mickey McManus, Peter Lucas & Joe Ballay

https://www.amazon.com/Trillions-Thriving-Information-Ecology-Everything/dp/1118484513

One of the earliest and most insightful examinations of pervasive computing, networked intelligence, sensor ecosystems, and the societal implications of abundant computation.

The Human Brand

Chris Malone & Susan Fiske

https://www.amazon.com/Human-Brand-People-Products-Companies/dp/1118611256

Research showing that people evaluate companies using many of the same cognitive frameworks used to evaluate other humans, particularly through the lenses of warmth and competence.

The Sovereign Individual

James Dale Davidson & William Rees-Mogg

https://www.amazon.com/Sovereign-Individual-Mastering-Transition-Information/dp/0684832720

A controversial but influential examination of how technology transforms power structures, institutions, capital formation, and governance.

The Ledger

Roger Ohan

https://www.amazon.com/Ledger-Important-Astray-Framework-Sovereign-ebook/dp/B0GX45G1LM

Insightful, urgent, and deeply provocative, The Ledger is more than a critique of economics; it is a call to action for every citizen to stop being a mere consumer of their country and start acting like a shareholder.

AI & Infrastructure Podcasts

NVIDIA Founder Jensen Huang on Inference

NVIDIA GTC Keynotes and Public Statements

https://www.nvidia.com/en-us/gtc/

Multiple presentations discussing inference workloads, accelerated computing, AI infrastructure, and the growing demand for compute resources.

International Energy Agency (IEA)

Energy and AI Research

https://www.iea.org/reports/energy-and-ai

Research detailing the growing energy demands of AI systems, data centers, electrical grids, and computational infrastructure.

GitHub Octoverse

Annual Developer and Software Activity Report

https://octoverse.github.com

GitHub’s annual report measuring software development activity, global developer growth, open-source adoption, and the acceleration of code production.

There is a moment early in the conversation where Chris frames the entire open office hours episode theme as a contradiction in the Knowing vs Doing gap.

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Americans over 50 know estate planning matters. They feel the anxiety. They see aging parents. They have kids, homes, retirement accounts, businesses, second marriages, prior marriages, blended families, passwords, insurance policies, healthcare decisions, and the slow realization that life is not as administratively simple as it used to be.

And yet many still have no basic documents in place.

Others have documents that are outdated.

Still others have documents that were created once, placed in a binder, and never reviewed again.

Meanwhile, the anxiety is often pointed at the wrong target. People worry about estate taxes, but the real risks are often more ordinary and more dangerous: no plan, stale documents, unfunded trusts, old beneficiary forms, long-term care costs, probate, family conflict, incapacity, digital lockout, and business succession that never got designed.

That is why Matt Chats exists.

Not to scare people.

To humanize the conversation before a crisis forces it.

Matt Meuli is not just a guest in this episode. He is Chris’s counsel, partner, and friend. That gives the conversation a different texture. It is not two people performing expertise at each other. It is one person asking the questions families actually ask when the camera is off, and another person answering from decades of experience helping clients navigate the uncomfortable intersection of law, money, mortality, family, control, and care.

Matt makes his disclaimer clear. This is not legal advice. His answers are educational. His opinions come from experience, but every family needs advice specific to its own situation.

Then he gets to work making the intimidating feel understandable.

Need to Talk?

Subscribe to Shields & Succession inside Wealth Matters 3.0 to stay alerted for future Matt Chats, live office hours, replays, and upcoming articles.

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If at any point reading this (or listening/watching) you want to book a human one-on-one pre-consult with Matt Meuli’s team you can talk to an actual human M-F at the numbers below:

Clients in all 50 States and Territories Call: 307-463-3600
Colorado Residents Only Call: 970-820-0090

Call, ask the question, and start the conversation before the hospital, courthouse, nursing facility, creditor, or crisis starts it for you.

Your “Estate” Is Just “Your Stuff”

The first breakthrough in the episode is linguistic.

Matt says many people do not even know what an estate is. They hear the word and picture Downton Abbey, castles, massive land, family dynasties, tax lawyers, and the kind of wealth they do not believe they have.

That misunderstanding is expensive. An estate is not only a mansion.

An estate is your stuff. (Your condo. Your car.Your bank account. Your retirement plan. Your family photos. Your passwords. Your phone. Your business. Your house. Your insurance policy. Your digital life. Your medical decision-making authority. Your unfinished obligations.

Estate planning is simply the orderly movement and management of that stuff from one stage to the next, whether that means incapacity, death, care, guardianship, inheritance, business transition, or family continuity.

Once Matt reframes it that way, the whole subject becomes less abstract.

The question is no longer, “Am I wealthy enough to need an estate plan?”

The question is:

“Who gets to make decisions about my stuff and my life if I cannot?”

That is the question most families avoid or forget to ask, because they don’t own Downton Abbey.

It is also the question that determines whether grief becomes compounded with chaos.

You Already Have a Plan. You Just Won’t Like It.

One of the strongest points in the episode is Matt’s warning that doing nothing does not mean there is no plan.

There is always a plan.

If you do not write one, the state you live in provides one.

That default plan may decide who receives your property, who has priority, who can act, who inherits, who gets left out, and who has to go to court. In simple situations, the default may feel tolerable. In real families, it can become absurd quickly.

Matt gives examples that make the risk tangible. A married person without children may assume everything goes automatically to the spouse. Depending on the state, parents may receive a share. Suddenly, a surviving spouse may co-own a home with in-laws.

In a blended family, children from a prior relationship may inherit alongside a current spouse. If a child is still a minor, the ex-spouse may end up managing the child’s share, creating the kind of emotional and legal entanglement no one would have chosen on purpose.

That is the danger of relying on the plan you never read and certainly weren’t consulted with when it was designed.

The state does not know your family story. It only knows the statute.

The Legacy of Unanswered Questions

Chris brings the point home with a line that sits underneath the entire episode: the problems you leave behind become part of your legacy.

That is a hard truth, but it is not meant to shame anyone. It is meant to clarify. If your family has to fight through confusion while grieving, that becomes part of the story.

If your spouse has to negotiate with your parents, stepchildren, creditors, or the court, that becomes part of the story.

If nobody knows where your accounts are, what your passwords are, who your advisor is, or what your wishes were, that becomes part of the story.

If your children have to guess whether you wanted to be kept alive, where you wanted care, or who was supposed to make decisions, that becomes part of the story.

Estate planning is not only about assets. It is about not forcing the people you love to make impossible decisions without a map.

The Smartphone Problem

One of the most practical moments in the conversation comes when Chris shares a personal story.

His phone and laptop became unavailable for several hours during a day when he had meetings and obligations. Nobody died. Nobody was hospitalized. It was not a catastrophe. But for seven hours, he could not access his email, accounts, contacts, or two-factor authentication. He could not remember most phone numbers. He could not get into the systems that run modern life.

It was a temporary inconvenience that revealed a permanent vulnerability. This is the new estate planning frontier most families underestimate.

It is not only where the will is.

It is where the passwords are.

It is who can access the phone.

It is whether anyone knows the two-factor authentication path and has a duplicate copy of the Authenticator app for all the accounts.

It is whether someone can find the bank accounts, crypto wallets, insurance policies, subscriptions, bills, documents, advisors, and medical contacts.

Matt sharpens the point. Chris was alive, awake, and able to troubleshoot. Imagine if he had been unconscious on the beach.

That is why every person needs a champion.

Someone has to know where to look, who to call, and what authority they have.

Talking to Parents Without Making It Weird

The second major theme is the conversation many adult children dread.

How do you ask your parents about their estate plan without sounding like you are trying to get your inheritance early?

Matt’s answer is simple and powerful: lead with “help”.

Do not begin with, “What am I getting?”

Begin with, “What information do I need so I can help you?”

The conversation should be framed around care, not entitlement. Adult children can ask whether parents need help paying bills, organizing documents, managing appointments, understanding where things are kept, or making sure someone has the authority to step in if needed.

It is also important to acknowledge that parents may not want to disclose exact dollar amounts. They may not want their children to know everything. That does not mean the conversation is impossible. Matt explains that parents can share structure without sharing every number. They can explain who has authority, where documents are located, what the wishes are, and what happens if care is needed.

The point is not to invade privacy. The point is to prevent chaos.

The Sibling Problem

Family planning becomes even more complicated when siblings are involved.

One child may live nearby. Another may live across the country. One may be organized. Another may avoid conflict. One may be the natural caregiver. Another may be financially anxious. One may assume everything should be equal. Another may believe fairness should account for years of caregiving labor.

Matt tells a story that captures the issue. A parent puts a caregiving child on a joint bank account and repeatedly says the child should divide the money among siblings after death. During life, the caregiver agrees. But after years of changing diapers, managing care, missing work, giving up income, and carrying the burden while siblings visited only occasionally, the emotional math changes.

The account legally belongs to the caregiver. And the caregiver starts thinking, “I earned this.”

Maybe they did. Maybe they did not.

But the problem was not solved in writing before grief and resentment entered the room.

That is why communication and structure matter. A good plan does not rely on exhausted people making perfect decisions after someone dies.

Asset Protection, Estate Planning, and Legacy Planning Are Not the Same Thing

Another valuable part of the conversation is Matt’s distinction between estate planning, asset protection, and legacy planning.

Estate planning is the orderly transition of your stuff.

Asset protection asks how that stuff is protected from creditors, predators, lawsuits, divorces, care costs, taxes, or poor decisions, either while you are alive or after assets pass to beneficiaries.

Legacy planning asks what happens beyond the legal documents. It deals with values, stewardship, family continuity, business transition, and the kind of imprint you want to leave.

These categories overlap, but they are not identical.

A basic estate plan may avoid probate and move assets to the next generation. A stronger plan may also protect beneficiaries by keeping inherited assets in structures that are harder for creditors, ex-spouses, lawsuits, or bad decisions to reach.

For someone seeking asset protection during life, the planning path may be different. It may involve giving up some level of direct control, using trustees, or creating structures in jurisdictions that allow stronger creditor protection.

The key is intention.

You cannot build the right structure until you know what problem you are solving.

Probate Is a Public Process, Not a Private Family Matter

Matt’s explanation of probate is one of the most memorable parts of the episode.

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Before you listen/read or watch, make sure you subscribe to Brent Johnson and Santiago Capital on Substack here:

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And subscribe to Brent’s YouTube channel, The Milkshakes Pod, here:

TL:DR Key Takeaways

Brent’s work sits at the intersection of global macro, monetary history, capital flows, currency markets, gold, Bitcoin, sovereign debt, and the strange gravity of the U.S. dollar.

He is best known for the Dollar Milkshake Theory, but this conversation is not just about a theory.

It is about the man behind it.

It is about the kid from western Nebraska who used to look up at airplanes and wonder where everyone was going, then grew up to build a framework for understanding where the world’s money goes when the system starts to shake.

Brent Johnson grew up in a small town in western Nebraska, far from Wall Street, finance, trading desks, and investment accounts. His father was an insurance salesman who worked for himself, which gave Brent an early model of independence, self-reliance, and eating what you kill.

He was not drawn to finance because he loved finance. He was drawn to finance because he was already fascinated by the world.

As a kid, Brent remembers looking up at planes flying overhead and wondering where the people on them were going. Years later, while flying from San Francisco to New York, he realized the flight path passed directly over the town where he grew up.

His early influences included history, storytelling, Michael Lewis’s Liar’s Poker, and the movie Wall Street. Those influences pulled him toward markets, but experience eventually taught him that Wall Street is not a place where the official story is always the truth.

One of Brent’s mentors, Simon Baker, taught him how to take the work seriously without taking himself too seriously. That lesson shaped how Brent survived the stress of markets without losing his humor.

A pivotal meeting before the Global Financial Crisis changed his career. A young, newly wealthy couple asked Credit Suisse executives simple but devastating questions about mortgage derivatives, real estate, hedging, and counterparty risk. Brent realized the clients understood the danger better than the people who were supposed to be the experts.

That meeting pushed Brent to stop repeating the company line and start thinking for himself.

He went back to textbooks, blogs, gold forums, Austrian economics, monetary history, and late-night self-study to understand how the monetary system actually worked.

The Dollar Milkshake Theory emerged from that long process. Brent came to see global finance as a relative game, where capital does not necessarily flow to the perfect place. It flows to the least bad place.

His core insight was that even though the U.S. dollar and U.S. system have serious problems, the rest of the world often has the same problems with fewer structural advantages. Because global debt, trade, funding, and settlement still depend heavily on dollars, stress can increase demand for dollars rather than reduce it.

The “milkshake” analogy came from There Will Be Blood: the U.S. has the biggest straw in the global system and can suck liquidity back into its own markets when the world prints money.

Brent originally expected the framework to lead to a sovereign debt and currency crisis by 2024. He openly says that his specific timing call was wrong. But he argues that many other implications of the framework have played out: higher interest rates, falling bond prices, higher gold prices, U.S. equity resilience, and continued dollar importance.

The framework has helped him remain invested rather than frozen in permanent crash fear. His approach is not to sit out markets waiting for collapse, but to own diversified assets while maintaining downside protection.

Brent’s portfolio worldview includes equities, real estate, gold, cash, and risk management. He sees gold not mainly as a de-dollarization trade, but as a response by countries and investors fleeing weakness in their own currencies.

A major theme is that de-dollarization is much harder than most people assume. The dollar’s network effects are embedded across trade, funding, liabilities, offshore demand, and global balance sheets.

Brent is preparing a major research paper called The Band, focused on why the dollar is so difficult to replace and why the global economy needs the dollar index to remain inside a functional range.

The deeper message: you do not need to agree with every timing call Brent has made to benefit from the framework. The value is learning how to see global markets through flows, relativity, incentives, balance sheets, liquidity, and the hidden plumbing beneath the headlines.

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This ATOMIQ LEVEL conversation with Brent Johnson is not just a macro interview. It is a story about a man who grew up far from the money centers of the world, became fascinated by where people were going, entered Wall Street through curiosity rather than pedigree, and eventually built one of the most debated monetary frameworks of the last decade.

It is about a kid in western Nebraska looking up at planes.

It is about a young advisor in New York walking across the city with an $18 million stock certificate in his briefcase and feeling, for one moment, like he owned the world.

It is about the intoxicating draw of Wall Street, the danger of repeating the company line, and the moment when a client’s simple question exposes that the so-called experts may not understand the machine they are standing inside.

It is about the long, lonely work of thinking for yourself. It is about why the dollar is not strong because America is perfect. It is about why capital often runs toward the least broken system when the rest of the world begins to crack.

It is about gold, Bitcoin, U.S. equities, real estate, liquidity, protection, risk, humility, and what it means to manage money when your framework is useful but your timing is never guaranteed.

Most of all, this conversation is about the difference between certainty and confidence.

Brent is not saying he has everything perfectly figured out. In fact, one of the most important parts of the conversation is his willingness to say where he got something wrong. But he has spent nearly two decades thinking about the dollar, the monetary system, global flows, and crisis dynamics for hours a day.

That kind of work does not produce certainty. It produces earned conviction.

Press play on this conversation with Brent Johnson of Santiago Capital if you want to understand why the dollar still matters, why de-dollarization is harder than the headlines suggest, why gold can rise without the dollar dying, and why a good macro framework should help you stay invested without pretending risk has disappeared.

Because the world’s money is always going somewhere.

The question is whether you understand where it runs when fear takes over.

Τhe Human Story Behind the Dollar Milkshake Theory

Before Brent Johnson became one of the most recognizable voices in global macro, before the Dollar Milkshake Theory became a phrase people argued about across podcasts, Substack threads, YouTube comments, and finance Twitter, before he became a person investors either loved, hated, misunderstood, or quietly stole from, he was a kid in western Nebraska looking up at airplanes.

That is where the story begins.

Not on Wall Street.

Not in a trading pit.

Not with a Bloomberg terminal.

In a small rural town where people worked on ranches, farms, the railroad, or in local businesses. His father sold insurance across western Nebraska and eastern Colorado. He worked for himself. He drove long distances. He carried the old independent salesman’s lesson that nobody owes you anything, and whatever you eat is usually connected to what you kill.

Brent absorbed that.

But he also wanted to see the world beyond the town.

He was not running from home. In fact, he speaks warmly about where he grew up. He did not hate the small town. He simply sensed that there was more out there. He would read the local newspaper hungry for information about places beyond western Nebraska. He loved history because history was story, and stories were how his mind held the world together.

Then there were the planes.

He remembers standing outside, looking up at them, and wondering where the people were going. Years later, living in San Francisco and flying to New York for work, he realized that the route passed directly over that same little town. From the window of the plane, he could look down and see where he had once stood.

He wondered if another kid was looking up. That image is the emotional key to this episode. The man who built a theory about where global capital flows began as a boy, wondering where people were going.

Finance Was the Vehicle, Not the Destination

Brent makes an important distinction early in the conversation. He did not become interested in the world because he was interested in finance.

He became interested in finance because he was already interested in the world.

That difference matters.

Some people enter markets because they love the scoreboard. Brent entered because finance became a way to study politics, history, trade, incentives, capital movement, human behavior, fear, ambition, and the power structures underneath everything else.

He could do the math. He could calculate ratios. He could understand accounting. But he was never merely a decimal-point person. He was a big-picture thinker, a pattern reader, a storyteller trying to understand why the system moved the way it did.

That is part of what makes his work compelling. It is not sterile macro. It is narrative macro.

It asks:

What is the story underneath the flows?

The Bad Influences That Told the Truth

Like many people who found their way into Wall Street in that era, Brent was shaped by some influences that were never meant to be instructional manuals.

He read Michael Lewis’s Liar’s Poker. He watched Wall Street. He absorbed the mythology of Gordon Gekko and Bud Fox, even while understanding later that those stories were warnings as much as invitations.

There is honesty in the way Brent talks about this. He does not pretend he was drawn only to noble motives. The swagger, the danger, the competition, the sharp elbows, the strange morality of markets, all of it had a pull.

But as he got older, he realized something more nuanced. Some of the flawed characters were wrong in how they lived, but not always wrong in how they observed markets.

Wall Street is not your friend.

That may sound harsh, but anyone who manages money long enough learns some version of it. Markets do not care about your intentions. Institutions protect themselves. Counterparties look after their own books. The official explanation is often less important than the hidden incentive.

Brent had to learn that the hard way.

The Moment That Opened the Door

There is a scene Brent shares that feels almost cinematic. Early in his career, he had pursued a large prospect for a long time. He sent information. He followed up. He kept trying. Then, late on a Friday afternoon in San Francisco, when most of the successful people had already left the office because the market had closed hours earlier, the phone rang.

It was the prospect.

The man asked why Brent kept sending him information.

Brent answered with the kind of young, hungry bravado that can either embarrass you or change your life.

“You should be my client.”

The man asked why.

Brent told him to give him a meeting, and he would explain.

The meeting happened. The client relationship eventually followed.

Those are the moments that make careers. Not because they are guaranteed to work, but because they test whether someone will take the shot when the door opens.

Brent understood that life comes down to moments. Markets do too.

The Mentor Who Taught Him to Laugh

One of the people who shaped Brent’s professional identity was Simon Baker, founder of Baker Avenue Asset Management. Brent describes Simon less as a formal mentor and more as a big brother figure: charismatic, successful, smart, English, cool, and unusually relaxed for a high-pressure business.

The lesson Simon taught him was not merely technical. It was existential. You can take the work seriously without taking yourself seriously.

That line matters. Brent manages money. He thinks deeply about risk. He has spent years wrestling with the dollar, debt, gold, currencies, and global markets. But he also laughs. He jokes. He talks trash. He admits mistakes. He does not pretend to be a marble statue of macro wisdom.

That ability may be one of the reasons he has survived the stress of being public with a controversial framework. If you cannot laugh in markets, markets will eventually eat you.

The Meeting That Broke the Company Line

The most important turning point in the conversation comes before the Global Financial Crisis.

Brent was working at Credit Suisse. His job was to find wealthy people and convince them to invest with the firm. He had developed a relationship with a young couple who had started a video game company from their Harvard dorm room and sold it for tens of millions of dollars.

They were smart…Very smart.

They did not know finance deeply, but they knew how to ask questions. For a couple of years, they told Brent they were not ready to place money because they wanted to learn first. So there was no immediate sales pressure. They talked. They learned. They became friends.

Eventually, they came into the Credit Suisse office in San Francisco. Brent arranged for the managing directors, research heads, alternative investment leaders, and the institutional “masters of the universe” to answer their questions.

It should have been a perfect meeting.

The office had views of the San Francisco Bay, the Golden Gate Bridge, and Alcatraz. The sun was out. The room was full of authority.

Then the questions began.

Why were real estate prices so high?

How could people making modest incomes buy million-dollar homes?

What were derivatives?

What were mortgage derivatives?

Did the firm trade them?

Wasn’t that risky?

How exactly was the risk hedged?

The executives gave answers that sounded confident but felt hollow. Then the wife asked the question that changed Brent’s life. If Credit Suisse had hedged the risk to other firms, which firms were on the other side?

The names came back: Goldman Sachs, Morgan Stanley, Merrill Lynch.

She leaned back and said they had been at those firms the week before, and those firms said they had hedged the risk to Credit Suisse.

That was the moment.

Brent realized she understood the circular risk better than the people who were supposed to be explaining it. He also realized he was not going to win the account. More importantly, he realized he had to stop outsourcing his understanding.

The Blank Sheet of Paper

After the meeting, Brent walked the couple to the elevator, said the polite goodbye, and returned to his desk.

Then he took out a blank sheet of printer paper and a pencil.

He began doing simple math. Real estate values. National debt. Tax revenue. Budget deficits. Deeply thinking about the questions the couple had asked. The basic relationships that should have made sense, but suddenly did not.

Then came the lightbulb moment. There was a problem. He did not fully understand the problem yet. But he knew three things.

1. There was a problem.

2. His bosses did not understand it.

3. And if his business was going to survive, he had to figure it out for himself.

That moment began the real education of Brent Johnson.

He went back to textbooks. He went into online gold forums. He read Austrian economics. He studied central banks, banking, money, balance sheets, history, and the plumbing behind the financial system. Night after night, after his wife went to sleep, he was on the computer reading, thinking, testing, and rebuilding his understanding from the ground up.

He had spent years repeating the company line. Now he was learning to think for himself.

From Crisis to Framework

When 2008 hit, Brent was not surprised in the same way many people were. He was not smart enough, as he says, to short the banks and become a billionaire. But he knew something was wrong, and he had positioned clients with a better understanding of the risks than he would have had before that meeting.

He left Credit Suisse in 2009 because the institution had not really changed. The crisis passed, and the business wanted to return to business as usual.

Brent could not.

The old model had broken for him. He had seen too much. He had already started building a different worldview.

By 2012 and 2013, he felt he had a much better understanding of how the monetary system worked. But he still had one major missing piece.

Relativity.

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The Least Bad Place

This is the heart of Brent’s framework. The world is relative. Capital does not always flow to the perfect place. In a crisis, it flows to the least bad place.

That insight changed how Brent saw everything.

He understood the problems in the United States: debt, deficits, political dysfunction, fiat debasement, money printing, falling purchasing power. But then he looked outward and realized that the rest of the world had many of the same problems, often with fewer advantages.

Other countries also had debt. Other governments also printed money. Other systems also had fragile banks, weaker freedoms, worse demographics, worse liquidity, worse property rights, or more complicated political risk.

The U.S. was not perfect.

It was simply the best piece on a damaged board.

And when global capital has to go somewhere, the “least bad” place can become incredibly powerful.

The Milkshake

That insight eventually became the Dollar Milkshake Theory.

Brent saw that there was more demand for dollars outside the United States than inside it. Global trade, debt, funding markets, offshore liabilities, and settlement systems all depended heavily on the dollar. If stress rose around the world and countries printed more money, that liquidity would not necessarily stay where it was created.

Some of it would get sucked back into the United States.

The analogy came from There Will Be Blood, where the oilman explains that he does not need to own the neighboring land if he can put a straw into his own land and drink the other man’s milkshake.

Brent thought that was a useful image for the global monetary system. The U.S. had the biggest straw.

If the world printed, the U.S. could still pull liquidity into its markets because the dollar sat underneath so much of the system.

That led him to a set of conclusions that frustrated many people because they did not fit neatly into the usual camps. Brent could believe fiat loses purchasing power over time and still believe the dollar could rise against other fiat currencies. He could believe gold matters and still believe the dollar is difficult to replace. He could see U.S. problems clearly and still think capital would flow into U.S. assets.

That is why the framework was so controversial. It forced people to think relatively, not religiously, about asset allocation.

Not Certain, But Not Unprepared

Brent is careful in this conversation to distinguish confidence from certainty. He has spent nearly eighteen years thinking about this framework for hours a day. That does not mean he cannot be wrong. It does mean most objections people raise are things he has probably already wrestled with.

He also admits where he was wrong.

He believed the framework would lead to a sovereign debt and currency crisis by 2024. That did not happen. He says so directly. In the money management business, timing matters. You cannot simply make the same prediction forever and pretend the calendar does not count.

But he also argues that many other implications of the framework have played out. Interest rates rose. Bond prices fell. Gold rose. U.S. stocks, though volatile, moved higher. Gold’s rise, in his view, has not primarily been about massive de-dollarization, but about countries and investors fleeing weakness in their own currencies.

That nuance matters. The framework did not deliver every prediction exactly as expected. But it helped him understand market behavior and stay invested without being paralyzed by collapse narratives.

That may be the most practical lesson for everyday investors.

A framework should not make you frozen. It should help you move with protection.

Staying Invested Without Being Blind

Brent’s approach is not to sit in a bunker waiting for the next Great Depression. He talks about owning equities, real estate, gold, and diversified assets while also maintaining downside protection.

That is an important distinction.

Many investors who understand monetary fragility end up in permanent fear. They read too much about debt, currency debasement, political dysfunction, and systemic risk, then sit in cash or disaster trades while markets continue to compound without them.

Brent’s framework helped him avoid that trap. He did not deny risk. He built protection. He did not abandon upside. He remained invested. He did not assume the dollar was flawless. He assumed the dollar was structurally important.

That is a more useful posture than the extremes.

The Dollar Is the Source Code

One of the ideas Chris brings into the conversation is that the dollar functions almost like source code for the global economy. That image fits Brent’s work well because the dollar is not just a currency in the simplistic sense. It is embedded in contracts, funding markets, debt structures, trade settlements, reserves, swaps, balance sheets, commodities, and global psychology.

That is why de-dollarization is so hard.

You cannot simply replace the dollar because a political bloc announces a desire to do so. You have to replace the network, the trust, the liquidity, the funding depth, the collateral system, the legal plumbing, the trade habits, the reserves, the market structure, and the emergency demand.

That does not mean the dollar cannot weaken. It does not mean the dollar system cannot change. It means that ripping it out is much harder than a headline suggests.

Brent’s forthcoming paper, The Band, goes directly into this problem. He explains that for the global economy to function, the dollar index has to remain inside a certain range. Too strong creates problems. Too weak, creates different problems. The world does not need the dollar to be perfect.

It needs the dollar to function. That is a different conversation than “the dollar is dead” or “the dollar can never fail.”

It is the middle path where the real work lives.

Gold, Bitcoin, and the Hard Asset Question

The conversation also sits inside a broader Wealth Matters 3.0 frame:

How do everyday investors think about hard assets, monetary inflation, gold, Bitcoin, real estate, equities, and cash in a world where fiat systems are designed to lose purchasing power?

Brent has long been an advocate for gold. He sees it as a monetary asset with deep historical durability. But he does not view gold’s rise simply as proof that the dollar is being rejected. In his framework, gold can rise because many countries and investors are fleeing their own currencies, even while the dollar remains globally important.

Bitcoin enters the conversation as part of the broader hard asset and sovereignty question. It may act as a risk asset, a commodity-like monetary asset, or a long-term hedge depending on the investor’s worldview and time horizon. But the key theme is not choosing one asset as a religion.

The key is understanding what each asset is supposed to do. Cash provides liquidity.

Gold can hedge fiat monetary disorder.

Bitcoin may offer asymmetric monetary optionality.

Equities with pricing power can participate in nominal growth.

Real estate can preserve value in specific forms and locations.

Protection matters because timing is hard.

That is the kind of portfolio conversation investors need now.

Not slogans.

Roles.

The Haters and the Work

Brent has taken plenty of criticism over the years. Some people mocked the Milkshake when the dollar weakened. Others accused him of missing de-dollarization. Some treated his framework as if it required the dollar to rise every day forever. Others misunderstood it as dollar maximalism.

Brent does not seem especially bothered.

He says he has pounded the table hard, so whatever comes his way, good or bad, he has earned some of it. He even likes the haters in a way because they keep him sharp.

But the deeper reason criticism does not shake him easily is the work.

He has spent the hours.

He has tested the thesis.

He has tried to disprove it (and will continue that effort).

He has updated it.

He has admitted where timing failed.

That is the difference between a pundit and a practitioner. A pundit needs to sound right today. A practitioner has to manage through tomorrow.

Brent’s confidence is not bravado. It is scar tissue.

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Markets, Milkshakes, and Madness

This episode earns its title because the world Brent describes often feels mad on the surface. Interest rates rise while people expect cuts. Gold rises while the dollar does not die. U.S. equities move higher while macro risks remain obvious. Debt grows. Liquidity expands. Inflation comes and goes through different channels. De-dollarization trends exist, but the dollar’s network effects remain stubborn.

The madness is real.

But the framework helps create order.

The Milkshake Theory is not valuable because it predicts every tick. It is valuable because it forces investors to ask better questions.

Where is the liquidity going?

What currency are debts owed in?

What happens when global stress rises?

Which system is least bad?

Where does capital hide?

What happens if the dollar gets too strong?

What happens if it gets too weak?

What does gold really signal?

What is protection versus speculation?

What is the difference between losing purchasing power and rising versus other fiat currencies?

Those questions are worth the price of admission and the time spent listening to this insightful conversation.

Closing Thought

This ATOMIQ LEVEL conversation with Brent Johnson is a reminder that the most useful market frameworks are not born from certainty.

They are born from discomfort.

A young couple asks questions that the “experts” cannot answer.

A blank sheet of paper exposes a problem.

A man realizes he has been repeating stories instead of understanding them.

A decade of late nights becomes a framework.

A framework becomes a lens.

A lens helps investors remain engaged in a dangerous world without pretending the danger is gone.

For investors, this episode is a reminder that global macro is not just about charts and forecasts. It is about flows, incentives, balance sheets, network effects, and relative safety.

For Bitcoiners and gold advocates, it is a reminder that hard money arguments still have to reckon with dollar plumbing.

For dollar bulls, it is a reminder that dollar strength does not mean America is problem-free.

For advisors and allocators, it is a reminder that clients need more than fear or optimism. They need frameworks that help them participate in upside while surviving downside.

And for anyone trying to make sense of the next decade, Brent offers a powerful lesson:

The world’s money is always moving.

When things are good, it chases opportunity.

When things are bad, it runs toward the least bad place.

Press play on this episode with Brent Johnson of Santiago Capital, subscribe to his Substack, and follow Milkshakes Pod on YouTube if you want to understand why the dollar’s role in the world is harder to unwind than most people think, why gold can rise without the dollar dying, and why a good framework can be wrong on timing but still invaluable in practice.

Because the market does not care what story you prefer. It cares where the money flows next. The real risk is doing nothing!

~Chris J Snook

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Connect with Eric Munson and Adit Ventures

Before you watch/listen or read, connect with Eric Munson and learn more about Adit Ventures here:
www.aditventures.com

Overview

Eric Munson’s career sits inside one of the most consequential arcs in modern finance and technology: from the fruit orchards of early Silicon Valley to Fairchild Semiconductor, from Genentech and Apple IPO history to Palantir, Spotify, SpaceX, defense technology, AI, big data, cyber, fintech, healthcare, and the private markets shaping the next generation of wealth creation.

His story is not just about venture capital.

It is about pattern recognition.

It is about what happens when someone grows up close enough to innovation to understand that every great technology wave looks obvious only in hindsight.

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TL;DR Key Takeaways

Eric Munson began life in Brooklyn before his family moved to Silicon Valley in 1971 when his father went to work for Fairchild Semiconductor, one of the foundational companies in both semiconductor history and venture-backed company formation.

Fairchild became a seedbed for generations of Silicon Valley legends, including people who would later help create Kleiner Perkins, Sequoia, Intel, and much of the modern venture ecosystem.

Eric later worked at Hambrecht & Quist, where he had a front-row seat to the public market emergence of companies like Genentech and Apple, watching Silicon Valley evolve from agricultural orchards into the innovation capital of the world.

His personal and professional story also carries deep emotional weight. His family lost loved ones on 9/11 through Cantor Fitzgerald, which later shaped his conviction around Palantir’s mission and the importance of technology that can protect families from a similar tragedy.

Adit Ventures was built from modest beginnings. The original 2014 partnerships started small, with roughly a dozen investors and around $1.5 million to $2 million, focused initially on Palantir and Spotify.

Over time, Adit deployed approximately $300 million of client capital, alongside about $35 million of its own capital, and returned more than $3 billion in cash and securities to investors.

Eric’s investment philosophy has remained consistent for decades: back the best entrepreneurs and managers building tools, solutions, and technologies that change how people live.

Adit’s long-term secular themes include AI, big data, cloud, cybersecurity, defense technology, educational technology, financial technology, healthcare, space, and other transformational categories.

Eric argues that AI may become the largest innovation wave he has seen because it transcends and compounds prior waves, including chips, PCs, mobile, software, cloud, and the internet.

He does not believe AI will lift every boat. Like the early internet, the first visible winners may not be the lasting winners. The most durable value may come from application-layer companies that use AI to solve specific problems in government, healthcare, defense, enterprise operations, education, and other verticals.

Eric emphasizes that venture remains a people business. Quantitative metrics matter, but qualitative judgment may matter even more.

His 10-step evaluation process includes five quantitative factors, such as growth potential, margin profile, scalability, competitive threats, and business economics, and five qualitative factors, including whether the company serves its customers, employees, shareholders, and the broader community.

Leadership matters. Eric repeatedly returns to character, courage, ethics, integrity, resilience, and the ability of founders to navigate difficult cycles.

He sees long-term investing as the only real way to capture the value of generational companies. Speculation and day trading are not how he built wealth.

He believes the private markets may continue offering mispriced opportunities, especially when fear, uncertainty, liquidity needs, secondary share availability, and timing create discounts in companies tied to long-term secular themes.

His optimism is grounded, not naive. He worries about the loss of humanity, individual rights, and ethical guardrails, but he remains deeply bullish on the human spirit, adaptation, technology, healthcare innovation, education, and the democratization of opportunity.

The deeper message: wealth creation in the next era will not come from chasing every hype cycle. It will come from finding the people and companies that turn enduring technology waves into lasting human value.

Why You Should Listen

This ATOMIQ LEVEL conversation with Eric Munson is not just a venture capital interview. It is a living bridge between the origin story of Silicon Valley and the next wave of AI-driven wealth creation.

It is about a man whose father worked at Fairchild Semiconductor, who grew up watching fruit orchards turn into the most important innovation ecosystem in modern history, who learned the craft of capital markets around firms like Hambrecht & Quist, and who later built Adit Ventures by finding private market access to companies like Palantir, Spotify, SpaceX, Airbnb, Lyft, Robinhood, Anduril, and other category-defining technology businesses.

It is also a story shaped by loss. Eric’s connection to Palantir is not merely financial. After losing family members on 9/11, he understood the human value of software that could help prevent future families from experiencing that kind of devastation. That context gives his investing worldview a seriousness that goes beyond returns.

Yes, this episode gets into venture performance, private market secondaries, AI, cyber, defense tech, founder evaluation, valuation discipline, and long-term secular themes.

But beneath the numbers is a deeper question:

How do you identify the companies that actually matter before the world agrees they matter?

Eric’s answer is not hype. It is not momentum chasing. It is not pretending that every AI company deserves a premium. It is a long-term discipline built around founders, markets, timing, character, technology waves, customer need, and the courage to own what the crowd doubts.

This conversation is for investors, founders, advisors, family offices, entrepreneurs, and anyone trying to understand how private market access, AI disruption, secondary liquidity, and generational technology cycles may shape the next decade of wealth.

Because the next great companies are already being built.

The question is whether you know how to recognize them before they become obvious.

The Pattern Recognition Behind Generational Technology Investing

Before Eric Munson became the founder behind Adit Ventures, before he helped deploy hundreds of millions of dollars into private technology companies, before Palantir, Spotify, SpaceX, Airbnb, Robinhood, defense tech, AI, and big data became part of his investing vocabulary, he was a kid from Brooklyn whose life changed when his family moved west.

It was 1971.

His father had taken a job at Fairchild Semiconductor.

At the time, Silicon Valley was not yet the polished myth that founders, allocators, and technology tourists now talk about with near-religious reverence. It was still agricultural land, fruit orchards, engineering talent, semiconductor ambition, military and government demand, and a cluster of people who did not yet know they were building the future.

Eric saw that transformation early.

He watched a place become a pattern.

And that may be the most important part of his story.

Most investors learn about innovation from charts, pitch decks, cap tables, and performance attribution. Eric learned it by proximity. His father’s world at Fairchild included people who would later help define venture capital, semiconductors, software, and the modern technology economy. The financial team included figures tied to the origins of Kleiner Perkins and Sequoia. The scientific and engineering ecosystem around Fairchild helped seed Intel and generations of future builders.

This was not just a company.

It was a root system.

From that root system came entire forests of innovation.

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From Orchards to IPOs

Eric later entered the business himself through Hambrecht & Quist, one of the iconic investment banking firms that helped bring emerging technology and life sciences companies into the public markets.

He had a front-row seat to the kind of companies that changed what investors believed was possible.

Genentech was one of them.

At the time, biotechnology was not yet the accepted industry it is today. Regulators and investors had real skepticism. The idea that genetic engineering could become a scalable commercial and medical force required proof, education, patience, and courage. Eric watched as Genentech helped change the life sciences industry and eventually contributed to a world where biotechnology would reshape disease management, drug development, and quality of life.

Then came Apple.

One year after the Genentech deal, H&Q helped take Apple Computer public. Again, this was not merely a transaction. It was a window into a wave.

Eric was watching new industries move from improbable to inevitable.

That matters because great technology investing requires the ability to live in the gap between those two states. When everyone knows the thing is inevitable, most of the easy return is already gone. The opportunity is in the uncomfortable middle, when the future is visible but not yet agreed upon.

Eric has spent much of his career in that middle.

The Weight Behind the Palantir Conviction

There is another part of Eric’s story that cannot be separated from the way he thinks about technology.

His family lost loved ones on 9/11 through Cantor Fitzgerald.

That tragedy sits quietly but powerfully behind his conviction in Palantir. For Eric, Palantir was never just an interesting data company with government contracts. It represented something more human: software that could help agencies identify threats, analyze complex data, and potentially prevent other families from experiencing the kind of loss his family endured.

That kind of personal connection changes the way a person sees value.

There is financial value, of course. Palantir became one of Adit’s most important investments. But there is also mission value, societal value, and protective value. Technology is not abstract when it can help defend lives.

That is one of the deeper threads running through this episode. Eric is not only talking about companies that grow revenues and expand margins. He is talking about companies that matter because they solve consequential problems.

That is a different investment lens.

And it is one worth studying.

The Small Beginning of Adit Ventures

Like many great investment stories, Adit Ventures did not begin at massive scale.

It began small.

Eric explains that the original Adit partnerships in 2014 were modest, with perhaps a dozen investors and roughly $1.5 million to $2 million. The early focus was simple and concentrated: Palantir and Spotify.

The story is important because it strips away some of the mythology around access and scale. Yes, Eric had decades of relationships, experience, and market knowledge. Yes, he had lived inside the technology capital markets ecosystem. But the actual beginning of Adit was not a billion-dollar platform. It was a small group of people putting capital into private companies they believed could become much larger.

Over time, that small beginning compounded.

Adit would go on to make dozens of investments, deploy approximately $300 million of client capital, invest its own capital alongside clients, and return more than $3 billion in cash and securities.

That is the kind of performance line everyone wants to quote.

But the deeper lesson is how it began:

With conviction.

With access.

With relationships.

With disciplined pattern recognition.

And with the willingness to buy into companies before the public market gave everyone permission to believe.

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GoPro, Spotify, and the Proof of Concept

Eric tells the story of an early GoPro investment that helped validate the model. He had sold some real estate, used part of the proceeds to buy private shares from someone connected to the founder, and acquired stock at roughly $4 to $6 per share. The company went public around $28 or $29, traded much higher, and the position was hedged at a significantly higher equivalent price.

His partners looked at that and said, in effect, “We would like to do more of that.”

Of course they did.

Buy at six. Sell much higher. Repeat if possible.

But the repeat is the hard part.

That is where Adit’s broader strategy came in. Palantir and Spotify were not random bets. They were companies tied to long-term secular shifts: big data, national security, streaming, software, new user behavior, and the transformation of how people consume digital services.

Spotify is a perfect example. Many people looked at it as a music company. Eric saw it as a technology delivery system. Its real innovation was not simply access to songs. It was user experience, near-zero latency, streaming infrastructure, and a new expectation for how digital content should work.

That distinction matters.

The surface category was music.

The underlying company was technology.

That is where investors often miss the point.

The Eight Themes

Eric’s investment framework is anchored in long-term secular themes. Adit has focused on areas including AI, big data, cloud, cybersecurity, defense technology, educational technology, financial technology, healthcare, space, and other sectors where technology changes how people live, work, protect, learn, transact, and build.

That thematic discipline matters because it creates a way to filter noise.

Every cycle has hype. Every wave has false starts. Every category attracts capital before the business models are fully mature. But long-term themes act like rivers. The individual companies may rise, fall, merge, fail, or become generational winners, but the directional flow continues.

Eric has lived through multiple waves: semiconductors, the PC revolution, mobile, software, cloud, the internet, social media, and now AI.

His view is that AI may be the largest wave yet because it does not merely sit beside the prior waves.

It runs through them.

AI compounds chips, cloud, software, data, cybersecurity, defense, healthcare, finance, education, and space. It becomes a horizontal force that changes how every vertical operates. But that does not mean every AI company wins. In fact, Eric is clear that AI will not be a ubiquitous rising tide lifting every boat.

That is one of the most important warnings in the conversation.

The wave is real.

The winners are not automatic.

Why the First Winners May Not Be the Last Winners

Eric compares today’s AI market to the early internet. In the first internet era, the most visible companies included browsers and portals: Netscape, Yahoo, AOL, and others. They looked like the future because, for a moment, they were the future.

But decades later, those early category leaders are not the dominant companies that captured the most durable value.

The bigger and more enduring outcomes came from companies that built application-layer businesses on top of the internet: Google, Meta, Amazon, and others that created specific, scalable, monetizable products and platforms using the underlying technology.

Eric believes AI may rhyme with that pattern.

The large language model companies are extraordinary. They are raising enormous capital, buying massive compute, and changing how billions of people interact with machines. But over time, the model layer may become more commoditized than people assume.

The durable value may emerge in the application layer.

The companies that use AI to solve specific problems in healthcare, government, defense, finance, enterprise productivity, education, data management, and other verticals may create the next great outcomes.

This is where the Palantir analogy becomes important. Palantir built value by managing disparate data sets and turning them into useful intelligence for mission-critical environments. In an AI world, the companies that can combine data, workflow, trust, security, domain expertise, and application-specific execution may become enormously valuable.

The model is not the whole business.

The solution is.

Venture Is Still a People Business

When Chris asks Eric how he evaluates entrepreneurs, Eric returns to a foundational point:

This is a people business.

Asset management is a people business. Venture investing is a people business. Private markets are a people business.

That may sound obvious until you remember how much of the modern conversation is now obsessed with prediction markets, quant models, AI agents, automated analysis, and data-driven scoring. All of those tools matter. Eric uses frameworks. He has a 10-step process. He cares about metrics, growth, margins, scalability, competitive threats, and business economics.

But the qualitative side may matter even more.

Who is the founder?

Have they been through difficult times?

Can they lead when capital dries up?

Do they serve the customer?

Do they serve employees?

Do they serve shareholders?

Do they serve the community in which they operate?

Do they have courage, ethics, integrity, and character?

That is the part AI cannot fully reduce to a spreadsheet.

Not yet.

Maybe not ever.

Because great founders do not only allocate resources. They metabolize uncertainty. They carry people through fear. They communicate mission. They make hard decisions under incomplete information. They take the pain when the market turns against them. They hold the line when cheaper, easier, more popular choices are available.

Eric’s examples are telling. He talks about Brian Chesky at Airbnb during the pandemic, when travel stopped and the company had to make painful layoffs. Chesky raised capital, preserved the company, communicated with empathy, offered severance and support, and made clear to employees that the crisis was not a reflection of their worth.

That kind of leadership matters.

Not because it sounds nice.

Because companies are human systems before they are financial instruments.

The Private Market Discipline

Eric is also clear about the difficulty of private market investing. Once you buy into a private company, you are long. Liquidity is limited. Exits take time. Rights of first refusal, transfer restrictions, administrative complexity, valuation uncertainty, and regulatory realities make it very different from buying and selling public equities.

That is why discipline matters.

Eric likes valuation cushions. He references the idea that buying at a discount gives an investor room for time delays, execution risk, and unexpected volatility. He is not interested in chasing everything at any price just because the theme is exciting.

That point is critical in the AI era.

There will be extraordinary companies.

There will also be overfunded companies, crowded companies, early winners that fade, model-layer businesses that commoditize, and application companies that fail to find durable distribution.

Eric’s approach is not to abandon risk. Venture requires risk. But the risk has to be underwritten with judgment, diversification, thematic conviction, founder evaluation, valuation discipline, and an understanding that the payoff may take years.

The long term is not a slogan. It is the only way this game works.

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Mispricing, Secondaries, and the Access Question

One of the most interesting parts of the conversation is the discussion of private market mispricing. As AI accelerates, SaaS companies face pressure, application layers shift, and investors become nervous, there may be more moments when good companies are temporarily mispriced because of fear, uncertainty, or liquidity needs.

That is where access matters.

A founder, early employee, family member, or early investor may need liquidity before the public markets arrive. A company may be fundamentally strong but caught in a cycle where the broader market does not know how to price it. A private secondary opportunity may appear quietly before public investors ever see the name.

This was part of the Adit story from the beginning. Secondary access to Palantir and Spotify created a path into companies that were already meaningful but not yet fully accessible to most investors.

That kind of access is not merely transactional.

It is relational.

That is why private markets remain difficult for ordinary investors, even accredited ones. The opportunity is not only knowing which companies matter. It is knowing how to get access, how to price the risk, how to handle the paperwork, how to evaluate liquidity, and how to diversify across enough positions so the portfolio can survive the misses.

Eric notes that Adit has had failures along the way. That honesty matters. The goal is not perfection, it is progress.

The goal is a disciplined portfolio of companies tied to themes large enough that the winners can more than compensate for the ones that do not work.

The Human Premium in an AI World

The conversation eventually turns toward AI’s impact on work, wealth management, and human value. Eric does not believe AI will simply put everyone out of work. He sees job disruption, of course. Every major technology wave changes labor markets. But he believes the humanistic traits become even more valuable.

Empathy.

Passion.

Courage.

Judgment.

Entrepreneurial spirit.

Ethics.

Anger when properly channeled.

The ability to think outside the box.

The ability to sit across from another person, understand their life, their goals, their fears, their family, their needs, and their constraints.

These are not easily programmable. They are not cleanly captured by an algorithm. They are the very things that make people worth backing.

This is one of the more important ideas in the episode. As AI makes quantitative analysis faster and cheaper, qualitative judgment may become more valuable, not less. If everyone has access to better data tools, the advantage shifts toward interpretation, trust, courage, relationships, and the ability to recognize which humans can turn tools into outcomes.

That is the human premium. And Eric’s career is a study in it.

Family, Loss, and What Technology Is For

Near the end of the conversation, the story becomes more personal. Eric talks about family, his sons, his upcoming marriage, and the next generation. He talks about building Adit for family and friends. He talks about the people he lost on 9/11. He talks about the importance of individual rights, humanity, and ethical leadership.

This part matters because it reframes the entire venture conversation. Technology is not supposed to exist only to create marks on a portfolio statement.

Technology is supposed to improve human life.

It should protect families. It should extend health. It should create educational freedom. It should make government more efficient. It should help solve hard problems in energy, defense, healthcare, and food. It should democratize access to tools and opportunity.

Eric is optimistic, but not blindly so. He knows technology can go wrong. He worries about the loss of humanity and the erosion of individual rights. He understands that the systems being built now will shape the world his children and future generations inherit.

That is why leadership matters.

That is why ethics matter.

That is why character matters.

The future will not be determined by technology alone.

It will be determined by the people who build, govern, fund, regulate, and deploy it.

The Triumph of the Human Spirit

Eric ends with optimism. Not the glossy, naive kind. The earned kind.

He has heard predictions of technology’s death before. He heard them in the 1980s. He heard them in the 1990s. He heard them after the dot-com crash. He has seen volatility, bubbles, recessions, rate cycles, valuation resets, pandemics, and public market skepticism.

And yet technology has remained one of the great engines of wealth creation.

More importantly, human beings keep adapting.

Eric describes the triumph of the human spirit as one of the great under-discussed themes. It does not always sell headlines. Fear sells more easily. But human adaptation is one of the most powerful forces in history. People learn. They adjust. They rebuild. They migrate. They invent. They educate. They survive. They create.

In an era where intelligence itself may become as ubiquitous as electricity, that adaptability becomes even more important.

The upside, in Eric’s view, is dramatic. Healthcare innovation could be breathtaking. Education could become more accessible. AI could optimize government, energy, defense, healthcare, and food systems. Productivity could improve. New companies could create extraordinary value. More people could access tools once available only to large institutions.

The glass is not only half full.

In Eric’s words, the glass is refillable.

Closing Thought

This ATOMIQ LEVEL conversation with Eric Munson is a rare window into how a long-cycle technology investor thinks about the next wave.

He has seen Silicon Valley before it had the name. He has seen semiconductors, PCs, biotech, mobile, the internet, cloud, software, big data, and AI. He has watched companies go from misunderstood to essential. He has watched public markets doubt businesses that later became generational. He has seen private markets misprice opportunities. He has seen leadership matter when models break.

And he keeps coming back to the same core truth:

Back the best people building the most important tools for the future.

For investors, this episode is a reminder that the AI era will create enormous wealth, but not evenly and not automatically.

For founders, it is a reminder that character, resilience, customer value, and mission still matter.

For advisors and family offices, it is a reminder that private market access can be powerful, but only when paired with discipline, diversification, and long-term thinking.

For anyone worried about the future, it is a reminder that technology is not the whole story.

Human beings are.

Press play on this conversation with Eric Munson of Adit Ventures if you want to understand how one investor reads the next great technology cycle through the lens of Silicon Valley history, private market discipline, founder quality, AI disruption, and the enduring human spirit.

Because the future will not belong to every company calling itself AI.

It will belong to the builders who turn intelligence into value, courage into leadership, and technology into something that actually serves human life.

The real risk is doing nothing!

~Chris J Snook

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We pulled the last quarter’s worth of survey data, search behavior, and the questions people are actually typing into Google and AI answer engines about getting their “affairs in order.” A clear pattern showed up — and it’s not the one most people expect.

The fear is real. The preparedness is not. And a surprising amount of the worry is pointed at a threat that, for most families, no longer exists.

Here’s what’s genuinely top of mind for Americans age 50 and up right now, what the data says, and where the real risk is hiding.

The 7 2026 Concerns Online Sentiment Revealed

1. “I know I should, but I still haven’t.” The knowing–doing gap is the #1 problem.

The largest annual study in the space — Trust & Will’s 2026 report, drawn from 5,000 U.S. adults surveyed in late January and early February — landed on a number that hasn’t moved: 56% of Americans still have no estate planning documents at all. Will ownership actually fell over the past year, down to 26%, even as trust ownership ticked up to 14%.

The kicker: 73% say estate planning is personally important. People aren’t unconvinced. They’re stuck. And 42% admit they wouldn’t know what to do if a family member died today — a number that jumps to 56% among those with no documents in place.

The most exposed group isn’t who you’d guess. Gen X carries the highest unprotected rate at 62% — the very generation now juggling careers, college-age kids, and aging parents at the same time. Boomers are the most prepared at “only” 48% unprotected, which is still nearly half.

The real question isn’t whether you need a plan. It’s what’s actually stopping you from finishing the one you started.

This is exactly the kind of stuck point we work through live every week.

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2. “How do I talk to my parents about their money — without it getting weird?”

If you’re 50+, you’re often planning two estates at once: your own, and your aging parents’. This is the search query that’s quietly exploding — the “sandwich generation” money conversation.

The numbers explain the anxiety. A late-2025 Finance of America survey found that among self-identified sandwich caregivers, 86% feel emotionally exhausted, 80% physically exhausted, and 69% financially exhausted — all up sharply from 2022. Nearly a third expect a parent to eventually move in, and a third have already been asked to help cover a parent’s expenses. Allianz’s data echoes it: 70% say caregiving has significantly hit their own retirement plans, and 65% worry they won’t have enough to retire because of it.

The avoidance is understandable — nobody wants to look like they’re circling the inheritance. But the cost of not having the conversation is brutal: scrambling through a parent’s paperwork mid-crisis, discovering there was no plan, or learning too late that long-term care quietly drained the estate everyone assumed they’d inherit.

The fix is almost always a structured, low-pressure conversation before it’s urgent — covering where the documents are, who’s named to make decisions, and what the wishes actually are. It’s a skill, not a confrontation.

3. “What happens if I need long-term care — and who pays for it?”

This is the single most underestimated line item in retirement, and the search data shows people are finally waking up to it.

The sticker shock is severe. Based on the most recent Genworth/CareScout and A Place for Mom benchmarks, the national median runs roughly $70,800 a year for assisted living, about $78,000 a year for an in-home health aide, and north of $108,000–$127,000 a year for a private nursing-home room — with costs rising faster than inflation. The Center for Retirement Research at Boston College estimates a typical 65-year-old should earmark around $165,000 for future care needs (closer to $171,000 for women, who tend to live longer and need care longer).

Here’s the misconception that wrecks plans: Medicare does not cover long-term care. It covers up to about 100 days of skilled nursing after a hospital stay — and that’s it. Custodial care, assisted living, memory care, and ongoing in-home help fall outside it entirely.

That leaves three real funding paths: self-fund from savings, transfer the risk with long-term care insurance (premiums run roughly $1,500–$3,500 a year for a healthy 55-year-old), or structure for Medicaid eligibility, which has its own strict look-back rules and timing requirements that have to be planned years ahead, not in a crisis.

The shield here isn’t the policy. It’s deciding — on purpose, in advance — which of those three doors you’re walking through.

Ready to reach out to Matt’s firm directly for a human phone call?

Ask specific questions in condidence about your Life and Legacy or Wyoming Asset Protection Trust structure Pre-Consult Call (Human’s answer during office hours M-F 9 am-5 pm MST):

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4. “I have a trust... so I’m covered, right?” (Probably not.)

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Tanvi’s work is some of the sharpest geopolitical and macro-strategy analysis I have found on Substack because she does something most headline commentary fails to do.

She watches what is actually moving beneath the noise.

Not the talking points.

Not the performative outrage.

Not the easy partisan explanation.

The deals. The incentives. The energy flows. The security architecture. The trade routes. The industrial policy. The quiet reordering of power before most people realize the world has already changed.

TL;DR Key Takeaways

Tanvi Ratna returns to the ATOMIQ LEVEL after her first appearance became one of the strongest-performing episodes of the show’s early run.

This conversation is a deeper field report from someone who has spent the last several weeks close to the front lines of the global realignment, including time in Europe, Eastern Europe, and around major diplomatic and economic meetings.

Her central argument is that the world is not merely experiencing chaos. It is experiencing a deliberate departure from the old liberal international order toward a more transactional, sovereignty-driven, mercantilist world.

A major theme is that many of the biggest deals and reordering moves are happening quietly. The most important parts of the strategy are often not the things being loudly broadcast.

Europe is being reshaped militarily, economically, and energetically. NATO responsibilities are shifting. Eastern Europe is being elevated. Poland, Croatia, Romania, Slovakia, Finland, Sweden, Italy, and the UK appear in the conversation as part of a different strategic map than the old Franco-German-centered Europe.

Energy is the foundation of the whole shift. As Europe moves away from Russian energy, American LNG, Eastern European ports, new pipelines, and energy infrastructure become strategic levers for the next phase of European security and reconstruction.

Croatia and Poland emerge as especially important nodes. Croatia is discussed as a growing energy and infrastructure base, while Poland is framed as a continental headquarters of sorts for the new strategic push.

AI data centers, energy infrastructure, technical talent, and geopolitical alignment are all converging. Tanvi describes Eastern Europe as not only strategically important, but also technically capable and cost-competitive.

The U.S. is not simply retreating from Europe. It is forcing Europe to take more responsibility while preserving key strategic capabilities such as nuclear umbrella support and broader coordination power.

The conversation then moves to China, the Quad, India, Japan, Australia, and the Indo-Pacific. Tanvi argues that public optics around China may suggest cordiality, but the post-summit moves suggest containment architecture is still being activated.

The Quad is framed as a renewed strategic platform, with maritime intelligence, critical minerals, supply chain cooperation, standards, telecom, digital identity, AI, and freedom of navigation all part of the emerging architecture.

Critical minerals become a major investment and industrial policy theme. Tanvi warns that building non-China supply chains will require more than rhetoric. It may require price floors, guaranteed demand, and coordinated industrial policy because China can undercut new entrants.

The deeper message is that we are moving from a world optimized for comparative advantage to a world optimized for sovereignty.

That changes everything.

Trade. Energy. Defense. AI. Critical minerals. Data centers. Supply chains. Capital allocation. Regional alliances. Investor opportunity. National strategy.

The most important line of the conversation may be Tanvi’s warning that when the economic and security layers begin moving together, the world order can change in just a few years, whether people are ready for it or not.

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Why You Should Listen

This ATOMIQ LEVEL conversation with Tanvi Ratna is not just a geopolitical interview. It is a field report from inside the quiet machinery of a world being reordered in real time.

It is about what happens when the old post-war assumptions stop working, when free trade is no longer treated as an unquestioned good, when countries begin optimizing for sovereignty as much as efficiency, and when the United States starts asking allies to carry more of the burden for their own security, energy, infrastructure, and industrial future.

It is about why Europe’s center of gravity may be moving east.

It is about why energy is not just a commodity.

It is about why AI is not just a technology story.

It is about why critical minerals are not just an investment theme.

It is about why China cannot be understood only through tariffs, trade deficits, Taiwan headlines, or summit optics.

It is about the return of grand strategy in a world that many people are still trying to explain through yesterday’s vocabulary.

Tanvi’s gift is that she does not let the conversation stay at the surface. She follows the incentives underneath the official statements. She watches what happens after the meetings, not just what gets announced during them. She understands that the real story may be hiding in which port gets funded, which command changes hands, which country becomes a new hub, which supply chain gets guaranteed, which ally gets elevated, and which energy route becomes unavoidable.

Most of all, this conversation is about seeing the shape of the next world before it is obvious.

Because by the time a new order becomes obvious, the best decisions have already been made by the people who saw it forming early.

Press play on this conversation with Tanvi Ratna if you want to understand why the next three years may reshape the global map of power, energy, AI infrastructure, critical minerals, and capital allocation.

Because the world is not waiting for the headlines to catch up.

Recognizing the Quiet Reordering of the World

Tanvi Ratna, Grand Strategy, and the Return of Sovereignty as the New Economic Stack

When Tanvi Ratna returned to the ATOMIQ LEVEL for Episode 37, it did not feel like a routine follow-up interview.

It felt like a dispatch.

Her first conversation on the show had already struck a nerve. It became one of the strongest-performing episodes of the early ATOMIQ LEVEL run, not because the subject matter was easy, but because Tanvi gave listeners something rare in a noisy world: a framework that made the chaos legible.

This second conversation begins with a different kind of energy. Tanvi has been moving. Europe. Eastern Europe. China-related summits. Quad meetings. Conversations with officials. Interviews. Closed-door rooms. The kind of travel and proximity that changes analysis from theory into pattern recognition.

She is not sitting back and commenting on headlines. She is watching the machinery move. And the machinery, in her telling, is moving much faster than most people realize.

The Deals Nobody Is Talking About

Tanvi begins with a striking observation. Some of the most important moves being made by the administration are not the ones being loudly promoted. In an era where nearly everything is broadcast, branded, leaked, clipped, and weaponized for attention, that fact alone matters.

The big things are happening quietly.

That is the first lens for the conversation. The loud story is Iran, China, tariffs, summits, personality conflict, and the surface-level drama of global politics. The quieter story is the actual reordering of the energy, defense, infrastructure, and industrial map.

Tanvi says she has seen this repeatedly over the last year of tracking the administration. Major deals are being made. Strategic architecture is shifting. But not everything is being announced in a way that fits the 24-hour news cycle.

That may be because the real objective is not applause.

It is leverage.

And leverage often works best before everyone knows exactly where it has been applied.

Europe Is Being Rewired

The conversation turns first to Europe, where Tanvi sees three layers of reordering: defense, energy, and economic infrastructure.

The defense layer begins with NATO. For years, American presidents have complained that Europe relies too heavily on the United States for security. This is not new. What Tanvi argues is new is that the rhetoric is now becoming operational.

Europe is being told, in effect, that it must take more responsibility for itself.

The United States may remain the ultimate coordinator in key areas. It may retain the nuclear umbrella. It may still provide heavy-lift capabilities and strategic support. But the days of the old blanket assumption are changing.

Tanvi points to quiet shifts in NATO command structures and the elevation of countries outside the traditional Western European core. This is not simply about France and Germany anymore. Poland matters. Italy matters. Finland and Sweden matter. The Arctic matters. The Mediterranean matters. Eastern Europe matters.

The map is changing. And if the map is changing, the investment thesis changes with it.

The End of the Old Europe Frame

For decades, many Americans thought of Europe through a Western European lens: Germany, France, maybe the UK, maybe Brussels, maybe the Eurozone as a political abstraction. Tanvi argues that this mental model is becoming obsolete.

The new strategic map is less sentimental.

It is about who is aligned, who is growing, who is willing, who is exposed, who is close to the front line, who has technical talent, who can host infrastructure, who can move quickly, and who can help build the next security and economic stack.

Eastern Europe becomes central in this frame. Poland is not a peripheral player. Croatia is not a scenic backdrop. Romania and Slovakia are not footnotes. Finland and Sweden are not merely new NATO members. These countries become part of the emerging architecture.

Tanvi describes the enthusiasm she saw among Eastern European leaders not as cautious consensus-building, but as something closer to execution energy.

They are not asking whether this should happen. They are asking how fast it can get going. That distinction matters.

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Energy Is the First Layer of Sovereignty

From there, the conversation moves into energy, because nothing else works without it.

Tanvi describes Europe’s move away from Russian energy as one of the great structural shifts that is underway. The logic is simple but profound: if Europe is going to reduce dependence on Russian supply, it must build new routes, new partners, new infrastructure, and new capacity.

That brings the United States into the center of the energy story.

American LNG. Eastern European ports. New pipelines. Energy flows through Croatia. Infrastructure extending toward Ukraine. Supply routes that help move countries out of the gray zone between Russia and Europe.

In this telling, energy is not merely an economic input. It is geopolitical architecture.

Energy determines who depends on whom. It determines who can be pressured. It determines who can rebuild. It determines who can stand apart from Russia. It determines which ports matter, which pipelines matter, which regions become strategic, and which countries suddenly find themselves at the center of a new map.

This is where Tanvi’s analysis becomes especially useful for investors and business owners. The energy story is not only about oil and gas prices. It is about where capital will flow, where infrastructure will be built, where political risk may fall, and where new industrial clusters may emerge.

Croatia, Poland, and the New Infrastructure Map

One of the most vivid parts of the conversation is Tanvi’s description of Croatia and Poland as strategic nodes in this emerging order.

Croatia, especially through its port and energy positioning, appears in the conversation as a key entry point for U.S. energy into Europe. From there, pipelines and infrastructure can move energy into Western Europe, Eastern Europe, and eventually toward Ukraine’s reconstruction.

Poland, meanwhile, is described as a kind of continental headquarters for much of the work. It is geographically central to the new security map, politically aligned, and increasingly important in the economic and defense architecture.

This is not the Europe many investors grew up analyzing.

This is not simply Germany plus France plus Brussels. This is a new strategic corridor. Energy, AI, defense, reconstruction, technical talent, and capital formation all begin to overlap.

That is where the signal is.

AI Data Centers and the New Economic Stack

Then the conversation widens. Energy infrastructure is not only about heating homes or replacing Russian gas. It is also about AI.

AI requires data centers. Data centers require power. Power requires infrastructure. Infrastructure requires political alignment, capital, permitting, ports, supply chains, and technical labor.

Tanvi describes a major AI data center push connected to the broader energy and infrastructure deals in Eastern Europe. She also notes that the technical talent base in Eastern Europe is real, and in some cases can be cheaper than Chinese talent.

That matters because the AI race is not only being fought in Silicon Valley. It is being fought wherever energy, talent, capital, and political alignment converge.

This is a crucial investor insight. The AI economy is not just a chip story. It is an energy story, a grid story, a data center story, a nuclear story, a talent story, a copper story, a permitting story, a security story, and a sovereignty story.

The new economic stack begins with watts.

Then it becomes compute.

Then it wields strategic power.

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From Comparative Advantage to Sovereignty

At the heart of Tanvi’s framework is a bigger claim: the world is moving away from the old model of comparative advantage as the dominant organizing principle.

For decades, the theory was that each country should produce what it was best at producing, trade freely, and allow global efficiency to create mutual prosperity. That was the worldview embedded inside the liberal international order, Bretton Woods institutions, globalized supply chains, and the post-Cold War economic consensus.

Tanvi argues that this world is changing.

Countries are no longer optimizing only for efficiency.

They are optimizing for sovereignty.

That means a country may produce steel even if it is not the cheapest steel producer, because it needs steel in a war. It may build domestic or allied critical mineral supply chains even if China can undercut them. It may invest in energy resilience even when markets would prefer cheaper dependency. It may build AI infrastructure not because it has an immediate comparative advantage, but because not building it means becoming strategically irrelevant.

This is the core of the conversation.

The old question was: What can we buy most efficiently?

The new question is: What must we control, produce, secure, or access no matter what?

That changes the world.

The America First System and Modern Mercantilism

Tanvi frames the new doctrine as a departure from the liberal international order into something closer to modern mercantilism. The Trump-era phrase may be “America First,” but the deeper structure is about balance of power, zones of influence, industrial policy, regional security, sovereign production, and transactional alignment.

That can look chaotic if you are still using the old language.

But if you look through Tanvi’s lens, the moves begin to make more sense. Pressure India over Russian energy, and it may look like an India story. But it may also be a Russia leverage story. Shift energy routes into Eastern Europe, and it may look like an infrastructure story. But it may also be a post-Ukraine reconstruction story. Pause or adjust Taiwan-related moves, and it may look like a concession. But it may also be part of a larger China negotiation.

The surface event is not always the point. The point is the objective.

And the objective appears to be a new order in which allies take more responsibility, adversaries are pressured across multiple fronts, and strategic supply chains are rebuilt around trusted blocs.

China and the Cloak-and-Dagger Summit

The China portion of the conversation carries a different tone. Tanvi is careful not to overstate what can be known, because the most important parts of great-power negotiations often do not show up in the communiqué.

She describes the China summit environment as almost cloak-and-dagger: public praise, vague optics, burner phones, security concerns, private signals, unexplained CEO presence, and few clear announcements.

But she also points to what happened after.

The Taiwan arms sales got paused. Reports emerge that China may be pressuring Russia on Ukraine. Secretary Rubio moves quickly into the Quad context. The containment architecture does not disappear. It evolves.

That is Tanvi’s method again. Do not just watch what leaders say at the summit. Watch what happens next.

The Quad Is Not Dead

The Quad, made up of the United States, India, Japan, and Australia, becomes another major theme. Publicly, the Quad is often described in soft language: economic cooperation, technology coordination, free and open Indo-Pacific principles.

Tanvi is blunt that it was originally formed, in part, as a way to contain China.

After the China summit, the question was whether the Quad was still alive. Tanvi argues that the answer is yes. In fact, it appears to be expanding its practical functions.

Near real-time maritime intelligence. Freedom of navigation. Critical minerals. Trusted supply chains. Standards. Telecom. Digital identity. AI usage. Indo-Pacific cooperation.

This is not just diplomacy. It is an operating architecture.

The Quad may not yet be openly militarized in the way some analysts speculate. Countries are still hedging with China. Nobody wants to say too much too soon. But the infrastructure of cooperation is deepening.

Again, the world is reorganizing quietly.

India as the Hard Counterweight

India occupies a special place in Tanvi’s framework because it is one of the few large countries fundamentally willing to oppose China economically and strategically.

India banned TikTok before the United States did. India has scale. India has a long-standing border and geopolitical tension with China. India sits inside the Indo-Pacific containment architecture. India also has its own sovereignty-first instincts, making it both a partner and an independent actor.

That makes India indispensable but not simple.

For investors, that is important. India is not merely an “emerging market growth story.” It is a strategic pillar in a post-China-plus-one world. It is part of supply chain diversification, digital infrastructure, critical minerals cooperation, maritime security, and regional balance.

But Tanvi does not let the optimism become lazy. India has its own complexity. Every country does.

The new order is not clean. It is negotiated.

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Critical Minerals and the Hard Reality of Industrial Policy

One of the strongest sections of the conversation comes when Tanvi turns to critical minerals. Everybody wants non-China supply chains.

Very few people understand how hard they are to build.

Tanvi makes the point that the narrative is easy: counter China, build trusted supply chains, develop critical mineral capacity, reduce dependency. But the business reality is harder. Why would a company enter a market if China can undercut it tomorrow?

This is where industrial policy becomes unavoidable.

If countries want trusted critical mineral supply chains, they may need to offer price floors, guaranteed demand, market share commitments, subsidies, financing, or other forms of support. Otherwise, private capital may hesitate to fund a project that can be destroyed by Chinese pricing power.

This is an essential investor takeaway. The critical minerals theme is real. But not every company will win.

Capital will not simply flow because the geopolitical narrative is attractive. The business model has to survive Chinese competition, policy uncertainty, permitting delays, capital intensity, and demand volatility.

In other words, the thesis is macro. The winners will be micro.

AI Capex as a Self-Fulfilling Global Cycle

Toward the end of the conversation, Tanvi gives one of the clearest explanations of why the AI buildout may become globally self-reinforcing.

The U.S. goes all in on AI capex. Data centers, chips, power, grid, nuclear, infrastructure. Other countries see this and begin to panic that they are missing the new economic stack. Suddenly, everyone wants data centers. Everyone wants critical minerals. Everyone wants nuclear. Everyone wants AI infrastructure. Everyone wants to build the next layer of the economy.

The United States does not need to persuade every country with a white paper. It simply moves first at scale. Then the rest of the world reacts. That is how a new economic stack becomes a self-fulfilling prophecy.

Tanvi’s warning is that when the economic layer and the security layer start moving together, the result is not a temporary policy cycle.

It is a new world order.

And once enough capital, infrastructure, alliances, and security commitments are in motion, reversal becomes much harder than people assume.

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The Three-Year Window

The most important line of the episode may be Tanvi’s suggestion that we could end up with a different world order in three years, whether people want it or not.

That is a startling claim, but by the end of the conversation, it does not sound dramatic.

It sounds logical.

If Europe’s defense responsibilities are shifting, if Eastern Europe is being elevated, if U.S. energy is replacing Russian energy, if AI infrastructure is being built around new power corridors, if the Quad is deepening, if critical mineral supply chains are being reorganized, if Gulf states are taking more responsibility for regional security, if countries are optimizing for sovereignty instead of pure efficiency, then the old order is not slowly fading.

It is being replaced.

Not in one treaty.

Not in one speech.

Not in one war-ending conference.

But through deals.

Ports. Pipelines. Commands. Data centers. Supply chains. Standards. Alliances. Price floors. Mineral factories. Maritime intelligence. Energy contracts. Security burdens. Capital flows.

That is how the new order arrives. Quietly at first. Then all at once.

Why Tanvi’s Substack Matters

This is why ‘s work matters so much right now. She is not offering lazy certainty. She is not pretending every move is perfectly knowable. She is not giving the audience a cartoon version of geopolitics where everything is either chaos or genius.

She is doing something more useful. She is tracking the pattern.

She is watching how the pieces move across regions, sectors, and strategic objectives. She is following the energy. She is following the defense architecture. She is following the trade routes. She is following the industrial policy. She is following the countries that suddenly matter more than they did before.

That is the kind of analysis investors need. Because by the time the financial media packages a new theme for mass consumption, the early signals may already be gone.

Closing Thought

This ATOMIQ LEVEL conversation with Tanvi Ratna is a reminder that the world does not reorganize itself through headlines.

It reorganizes through leverage.

Through energy.

Through ports.

Through pipelines.

Through military commands.

Through strategic minerals.

Through data centers.

Through alliances.

Through the countries willing to move first.

For investors, this episode is a reminder that geopolitical analysis is no longer optional. Energy, AI, defense, critical minerals, supply chains, and sovereign industrial policy are now deeply intertwined.

For business owners, it is a reminder that globalization is not ending, but it is being repriced around trust, resilience, and national interest.

For citizens, it is a reminder that the old language may no longer explain the new reality. And for anyone trying to understand the next decade, Tanvi offers a powerful lens:

Stop looking only at the speeches. Watch the deals.

Press play on this conversation with Tanvi Ratna, subscribe to her Substack, and study her work if you want to understand the reordering while it is still forming.

Because the next world order may not announce itself. It may simply get built while everyone else is arguing about the noise.

The real risk is doing nothing!

~Chris J Snook

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Joel’s work has always lived at the intersection of curiosity, creativity, faith, technology, play, reinvention, and making complicated things feel simple enough for normal humans to actually use. That is why this conversation matters now.

Because AI is not just another tool.

It is the latest disruption in a career built by a man who has survived, studied, and reinvented himself through the web, online gaming, Google AdSense, social media, podcasting, crypto, NFTs, and now artificial intelligence.

TL;DR Key Takeaways

Joel Comm describes himself as independent, strong-willed, curious, playful, and deeply shaped by a spiritual awakening in his mid-twenties that gave him a moral foundation for the rest of his life.

His entrepreneurial path began in the early 1990s as a mobile DJ, radio voice, nightclub DJ, and technology enthusiast. He bought his first computer, a TRS-80 Model 1, in 1980 at age sixteen and was already dialing into bulletin board systems decades before most people understood the internet.

Joel built his first website in 1995 and eventually created ClassicGames.com, a multiplayer JavaScript game room that grew to thousands of players and was acquired by Yahoo in 1998.

He has written 16 books, with his 17th, AI Made Simple, coming out in December. His work has been read around the world, and he has spoken globally by making complex technology accessible, practical, and fun.

Joel’s career has been shaped by repeated disruptions: the web, online gaming, Google AdSense, social media, mobile, live video, blockchain, crypto, NFTs, and AI.

He co-created The Bad Crypto Podcast with Travis Wright in 2017 after a season of uncertainty and serendipity. The show became one of the longest-running crypto podcasts in the world, with more than 10 million downloads.

Joel’s operating philosophy comes from his book The Fun Formula: be curious, take risks, and trust the process.

In this episode, Joel introduces his Disruption Confidence Cycle, a five-stage framework for navigating technological change: disruption, doubt, clarity, confidence, and momentum. You can download his free deep dive report on that framework here:

Joel openly shares that even after decades of reinvention, he has had seasons where he wondered whether his best work was behind him.

The AI wave created that same doubt again. At first, Joel used AI but did not feel fully claimed by it. Then, in early 2026, he began building with AI tools like Claude, OpenClaw, and Claude Code, and everything changed.

By asking AI to guide him “like a fifth grader,” Joel set up tools, built websites, created games, launched experimental projects, and became a practitioner rather than just a commentator.

That practitioner shift became the source of his new clarity, confidence, and momentum.

Joel now hosts AI for Everyone, a show designed especially for people around age 55 and older who feel intimidated, confused, skeptical, or frightened by AI.

His message is not that everyone needs to become technical. It is that everyone needs enough reps to see what AI can help them create, understand, simplify, or improve.

The deeper message: Joel Comm’s story is not about chasing every shiny object. It is about staying curious enough to find your next chapter before the world writes you out of it.

Why You Should Listen

This ATOMIQ LEVEL conversation with Joel Comm is not just an AI interview. It is a story about a man who has spent more than four decades riding the edge of technological change, not because he had a perfect plan, but because he refused to stop being curious.

It is about a kid who bought a TRS-80 in 1980, became a mobile DJ, built websites before most people knew what a website was, sold an online game platform to Yahoo, wrote books that taught the world how to monetize the early web, helped millions of people understand crypto through The Bad Crypto Podcast, rode the NFT wave, lived through the winters, and then found himself asking the question every creative leader eventually asks:

Is my best work behind me?

It is about why the answer was no.

It is about how AI reawakened Joel’s builder instinct once he stopped merely watching the tools and started using them to make things. Websites. Games. Calculators. Speaker platforms. Educational tools. Experiments. Proof that the cost of trying has collapsed.

It is about why older leaders, founders, creators, business owners, advisors, and professionals may have more advantage in the AI era than they realize, because pattern recognition only comes from living through prior disruptions.

It is also about why AI does not have to feel cold, technical, alien, or overwhelming. Joel’s mission with AI Made Simple and AI for Everyone is to make artificial intelligence simple, easy, useful, and fun for everyday life, especially for people who feel like the whole conversation has already passed them by.

Most of all, this conversation is about creative renewal.

The kind that arrives after doubt. The kind that only shows up when you are willing to play again.

The kind that reminds you that your experience is not obsolete just because the tools have changed.

Press play on this conversation with Joel Comm if you want to understand how a lifelong digital pioneer navigates reinvention, why AI may be the greatest creative empowerment tool of our lifetime, and how to move from disruption to doubt, from doubt to clarity, from clarity to confidence, and from confidence to momentum.

Because the future does not belong only to the youngest coder in the room. It belongs to the people who keep putting in the reps.

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The Man Who Turned Disruption Into a Playground

Before Joel Comm became a bestselling author, global speaker, digital pioneer, crypto podcaster, AI educator, and one of the more enduring explainers of emerging technology on the internet, he was a young man with no clear map.

He came from a broken home. He made his way through college without much direction, swept along by culture, partying, confusion, and the drift that can define a young life before it finds its center. Then, in his mid-twenties, something shifted. Joel found spirituality in the person of Jesus Christ, and that encounter gave him what he describes as a moral ground to stand on.

It did not fix everything. He is honest about that.

He does not pretend faith turned him into a flawless person. He says he is still very good at screwing things up. But it gave him a foundation. A place to build from. A line underneath the chaos that allowed the rest of his life to begin taking shape.

That matters because Joel’s story is not merely about technology. It is about orientation. The tools changed. The platforms changed. The markets changed. The industries changed. But the man stayed anchored by a few repeatable instincts: curiosity, play, risk, faith, humor, and a willingness to try the next thing before the crowd understood why it mattered.

The Voice Before the Website

Joel’s first entrepreneurial gig was not a startup, at least not in the way people use the word now. It was as a mobile DJ.

That detail feels almost too perfect. Before he was explaining the internet, before he was writing books, before he was podcasting to millions, before he was teaching people about crypto or AI, he was already learning how to hold attention, read a room, move energy, and use his voice.

He did radio. He did nightclubs. Eventually, he realized he could make more money with his own gear doing private parties, and he performed hundreds of them.

That was one side of Joel.

The other side was the kid who bought his first computer in 1980 at age sixteen, a TRS-80 Model 1 with 4K of RAM and a cassette player for storage. To save a program, you typed the command and recorded it onto magnetic tape. To load it, you played it back.

It sounds primitive now. At the time, it was magic.

Joel was dialing into bulletin board systems in 1980, which means he has been in the online world for more than four decades. Long before most people thought of digital life as normal, he was already there, experimenting, wandering, tinkering, asking what this machine could do.

That is the beginning of the pattern. Joel rarely waits for the world to explain the toy. He picks it up and starts playing.

The First Website and the Yahoo Exit

In 1995, Joel built his first website. He sensed that the internet was the next big thing, not because he had a crystal ball, but because he had enough curiosity to feel the shift before it had fully become obvious.

By 1997, he had a family-friendly website with software reviews and web games. He has always loved games, and that love would become one of the earliest meaningful inflection points in his career.

His webmaster introduced him to a young graduate at UC San Diego who had created the foundation of what might have been one of the world’s first JavaScript multiplayer game rooms. Friends were testing games like Hearts, Spades, Chess, and Backgammon. Joel saw the possibility immediately.

They partnered. They named it ClassicGames.com. They expanded it to sixteen games and grew it to thousands of players.

Then Yahoo bought it in 1998.

His partner went to work for Yahoo as what Joel jokingly calls the “chief game Yahoo.” Joel took cash and walked away, something he now describes with the self-deprecating wisdom of hindsight. His partner may not have needed to work another day in his life. Joel took what was, at the time, the most money he had ever seen.

Still, that exit changed his life. It got him out of debt, paid off his house, paid off credit cards, and put him in a position he has managed to preserve ever since: his head above water.

That may not sound like the Silicon Valley version of success, where every story has to end in nine or ten figures. But Joel’s measure has never been only money. In fact, he says clearly that if wealth had been his primary motivation, he probably would have focused on one thing and ridden it harder.

But that is not Joel. Joel is not the guy who wants one plate.

He is the guy who spins many because each one teaches him something new.

The Man Who Could Not Stop Playing

Joel has written sixteen books, with a seventeenth on the way. He has spoken around the world. He has built products, launched platforms, hosted shows, created content, experimented with tools, and lived through nearly every major digital disruption of the last thirty years.

The web.

Google AdSense.

Social media.

Mobile.

Live video.

Blockchain.

Crypto.

NFTs.

Artificial intelligence.

He did not always see every opportunity perfectly. He missed things. He passed by Bitcoin at first because the idea of mining did not click for him. He took cash instead of Yahoo upside. He has had projects that did not become what he hoped. He has had lean years. He has had seasons where the well went dry.

But what makes Joel compelling is not that he always wins. It is that he keeps returning to curiosity.

That is the heartbeat of his career. If something looks interesting, he wants to know what it can do. If it can help him create something cool, he wants to play with it. If he figures something out, people start asking how he did it. Then come the books, blogs, talks, shows, newsletters, interviews, and teaching.

That is the Joel Comm loop. Curiosity becomes experimentation. Experimentation becomes discovery. Discovery becomes explanation. Explanation becomes service.

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The Wilderness Before Bad Crypto

One of the most honest parts of this conversation is Joel’s willingness to talk about the in-between seasons. Not the big win. Not the big launch. Not the moment when the audience is growing and the phone is ringing.

The dry places.

In 2017, while writing The Fun Formula, Joel was in one of those wilderness seasons. The book’s own thesis was challenging him while he was writing it. Be curious. Take risks. Trust the process. Wait for serendipity.

But waiting is not easy when you are the one doing it.

Joel was wondering what came next. He was not actively chasing some new massive thing. He was trying to trust the process he was telling other people to trust.

Then came Travis Wright.

Joel and Travis had been messaging back and forth during the 2016 election cycle and realized they shared some similar views. After the election, Travis asked Joel what he thought about Bitcoin. Joel had heard of it, but had not fully understood it. Mining confused him. The whole idea seemed strange.

So they began learning together.

Then Travis joked that maybe they should take the conversation public and start a podcast.

Joel said, “Let’s talk.”

Two days later, the first episode of The Bad Crypto Podcast was out. And it blew up.

The Genius of Being Bad

The name was perfect because it removed the expert burden immediately. They were not saying, “We know everything.”

They were saying, “We are figuring this out in public, and you can come with us.”

That made the show accessible at exactly the right time. They launched in July 2017, just as the crypto bull market was going wild. The audience rode the wave with them. Then the market crashed. Then came the crypto winters. Then came NFTs. Then came another cycle. Through all of it, they kept publishing.

That may be one of the most important lessons from Joel’s story.

The wave matters. But the work matters more.

The Bad Crypto Podcast became one of the longest-running crypto podcasts in the world, now moving toward its tenth year with more than 10 million downloads and listeners around the globe. But its durability came from more than timing. It came from genuine fascination.

Joel and Travis were not pretending to care.

They cared.

They were learning in real time, and the audience could feel it.

Curiosity, Risk, and Trust

Joel’s framework from The Fun Formula is simple: be curious, take risks, and trust the process. Those three ideas sound easy until you have to live them.

1. Curiosity means allowing yourself to explore before you know the payoff.

2. Risk means stepping outside guaranteed income, stable expectations, social approval, and familiar identity.

3. Trust means not forcing the next chapter before it is ready to arrive.

That last one may be the hardest.

Because builders build. Creators create. Entrepreneurs push. Marketers market. Leaders want momentum. When momentum disappears, the silence can feel like judgment.

Joel knows that feeling. He has had moments where he has asked whether his greatest work was behind him. He has had seasons where the doorbell stopped ringing, the speaker requests slowed, the next big thing did not immediately reveal itself, and he wondered whether he was done.

Then disruption arrived again. This time, it was AI.

The Disruption Confidence Cycle

In this conversation, Joel introduces a framework he calls the Disruption Confidence Cycle.

It begins with disruption. Something changes. The web appears. Mobile arrives. Social media reshapes distribution. Blockchain creates a new money and ownership layer. AI begins democratizing intelligence. The world moves, and suddenly, what used to work no longer feels as stable.

Then comes doubt. Leaders ask themselves whether they are stupid for not seeing it sooner, foolish for trying it, or obsolete if they do not. They question their relevance. They wonder whether anyone will still care what they have to say, sell, teach, or build.

Then comes clarity. After enough pattern recognition, the experienced builder says, “Wait a second. I have been here before.” The details are new, but the shape is familiar.

Then comes confidence. The fundamentals remain. Curiosity still works. Experimentation still works. Judgment still matters. The tools may be new, but the human capacity to learn and apply them is not.

Finally comes momentum. Experience becomes an advantage. The person who has lived through multiple cycles starts integrating new tools with deeper judgment and begins moving again.

That is Joel’s gift in this episode. He does not talk about disruption like someone reading a trend report. He talks about it like someone who has lived the cycle enough times to recognize the emotional weather.

Disruption.

Doubt.

Clarity.

Confidence.

Momentum.

That is the map.

Joel also shared a free deep dive report on the elements of this framework, which you can download here if you haven’t already:

AI and the Question of Relevance

After moving to Puerto Rico in 2021 with his fiancée, Erin, Joel found community, beauty, and a different rhythm of life. The NFT market, his latest major creative wave, eventually collapsed. He still believes in digital collectibles, but the hype, greed, and crash changed the opportunity.

For a while, he was semi-retired. But Joel is not wired to stop creating.

By 2024 and 2025, he began feeling the discomfort again. The phone was not ringing the same way. He was not being asked to speak as much. Nobody was asking him to write books. He had been around enough disruptions to know AI mattered, but at first he could not quite find his place in it.

He used AI.

He watched AI.

He experimented with AI.

But it did not fully click.

The doubt returned.

Was he done?

Was AI the thing, and had he somehow missed his door into it?

Then came the practitioner moment.

“Talk to Me Like I’m a Fifth Grader”

In early 2026, Joel began seeing people on X and LinkedIn using OpenClaw and Claude Code. He did not know if he could set it up. He did not know how to code. He did not pretend to understand all the moving parts.

So he asked Claude to walk him through it like he was a fifth grader.

That one decision changed everything.

The AI told him to open a terminal. Copy this. Paste that. Find a host. Try this. Fix that error. Keep going. Within about two hours, Joel had an OpenClaw set up and doing a task for him.

Then he wondered whether he could build a website.

He had an artificial intelligence top-level domain sitting unused: artificialintelligence.studio. He used Claude Code to build out a site with four tools on it.

It was rudimentary. But it was live. And he built it.

That changed his relationship with AI. He was no longer only a user. He was a builder. He was a practitioner. The dopamine centers that had fired during every major creative exploration of his career lit up again.

The confidence returned because the reps returned.

Building for the Joy of Building

Once Joel became a practitioner, the projects began multiplying. He built tools. He built websites. He built games. He experimented with AI-generated infographics. He used tools like Google’s NotebookLM, Claude design features, and new image generation models to create things that previously would have required hiring designers, developers, coders, and teams across time zones.

He built a site called GrowingProfits.com with dozens of AI-powered tools and original content. He created free calculators and evaluators, including tools for entrepreneurs and side hustle ideas.

He built daily word games under AI for Everyone, inspired by the kind of daily puzzle experiences he and Erin enjoy.

He even created a retro-style 3D shooter game called Pound Break, where players rescue dogs and shoot bad guys with a water gun.

Was he trying to turn each of these projects into a venture-backed company?

No.

That is not the point. The point was the reps. The point was proof-to-himself.

The point was finding out what was possible when the cost of experimentation had collapsed to nearly zero.

This may be one of the most important takeaways for entrepreneurs, creators, advisors, and business owners right now. AI does not just reduce the cost of production. It reduces the cost of failure. It reduces the cost of curiosity. It allows a person to turn a dormant idea into a working prototype without waiting for permission, budget, staff, or a perfect plan.

That does not mean every idea should be built.

Joel and Chris both acknowledge the shadow side. Hyper-creative people can suddenly find themselves with fifty possible projects because the old constraints are gone. Just because you can build everything does not mean you should.

But before discipline comes discovery. And discovery requires reps.

AI for Everyone

Joel’s latest mission is AI for Everyone, a show and educational platform aimed especially at people around age 55 and older who feel intimidated, confused, frightened, skeptical, or simply out of the loop.

That audience matters because Joel understands something many AI insiders forget.

Our feeds are not the world.

The people posting endlessly on X about agents, coding tools, model releases, and AI workflows are not representative of the majority of humans. Most people are not trying to keep up with every new frontier model. They are not building with Claude Code. They are not using OpenClaw. They are not comparing image model outputs or creating AI-powered web apps.

Many are overwhelmed. Many feel behind. Many assume AI is for someone else.

Joel’s work is designed to meet them where they are. His upcoming book, AI Made Simple: Artificial Intelligence for Everyday Life, is written for that audience. It is not intended to become obsolete the moment a new model ships. It is written to empower people to think about how AI can be used in their business, their life, their creativity, their communication, and their everyday routines.

That is Joel’s lane. Not fear. Not hype.

Practical empowerment.

Simple. Easy. Useful. Fun.

The Advantage of the Experienced

A powerful thread running through this conversation is the idea that older leaders may have an advantage in AI if they stop disqualifying themselves.

Younger people may be faster with tools. They may adopt new interfaces more naturally. They may have less fear of experimentation. But experience has a pattern recognition advantage.

Joel has lived through enough cycles to know that no disruption stays frozen in its first form. The web changed. Social media changed. Crypto changed. NFTs changed. AI will change, too. What works today will not work forever. What looks like magic today will become infrastructure tomorrow.

The seasoned person has seen that before.

That matters because AI is not only a toolset. It is a new cycle of disruption, and cycles reward those who can move through emotional turbulence without losing themselves.

The question is not whether you can become a twenty-three-year-old coder. The question is whether you can become a practitioner with the experience you already have.

Joel’s answer is yes. And he is proving it by building in public.

The Reps Are the Strategy

Near the end of the conversation, Chris frames the moment clearly. A year from now, the latest frontier models may be able to produce the equivalent of thousands of hours of high-quality work in minutes. Even if innovation slows dramatically, the capability curve is still moving faster than most institutions, companies, or individuals can absorb.

That means the reps matter now. Not because every experiment becomes a business. Not because every project becomes a product. Not because every prompt produces genius. The reps matter because they build muscle memory.

They reduce fear.

They create pattern recognition.

They help you find your place.

Joel’s story is a living example. He did not reason his way into confidence from the sidelines. He built his way into it. He asked the tool to guide him like a beginner. He allowed himself to look foolish. He made simple things. Then graduated into more complex things. Then useful things. Then playful things. Then teachable things.

That is how the cycle moves. Disruption becomes doubt. Doubt becomes clarity. Clarity becomes confidence. Confidence becomes momentum.

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Closing Thought

This ATOMIQ LEVEL conversation with Joel Comm is a reminder that reinvention is rarely clean while it is happening.

From the outside, a career like Joel’s can look like a series of smart moves: early computers, websites, Yahoo Games, books, Google AdSense, podcasting, crypto, NFTs, AI.

From the inside, it is more human.

Broken beginnings.

Faith.

Curiosity.

Risk.

Mistakes.

Exits.

Lean years.

Dry wells.

Serendipity.

Doubt.

Play.

Repetition.

Renewal and Reinvention.

Joel’s story matters because he does not pretend the AI moment is easy. He does not pretend everyone should become a technologist. He does not pretend that the tools are not overwhelming. He does not pretend he never wondered whether his best days were behind him.

He simply found his way back into motion.

For entrepreneurs, this episode is a reminder that the next wave may not arrive as a business plan. It may arrive as a toy you cannot stop playing with.

For creators, it is a reminder that your curiosity is still an asset.

For older professionals, it is a reminder that your experience is not obsolete. It may become your advantage if you combine it with new tools.

For business owners, it is a reminder that the cost of experimentation has collapsed.

And for anyone feeling overwhelmed by AI, it is a reminder that you do not have to understand everything.

You just have to start. Ask the tool to explain it like you are a beginner. Build something small. Take the reps. Find the fun.

Press play on this episode with Joel Comm, subscribe to his Substack, get AI Made Simple, and download the free Disruption Confidence Cycle report if you want to understand how a lifelong digital pioneer turned another disruption into another playground.

Because the future is not waiting for you to feel ready.

But the tools are ready to help you begin. The real risk is doing nothing!

~Chris J Snook

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Thank you to everyone who tuned into my live video! Join me for my next live video in the app and subscribe!

Share Wealth Matters 3.0

Gratitude for a great conversation!

Before you read the show notes below,

1. Please subscribe to Roger

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2. And get Roger’s book, The Ledger: How Important Assets Go Astray and a Framework for Sovereign Wealth
   

Roger’s conversation is a masterclass in practical understanding of what truly drives a nation’s (or family’s) wealth. His work is built around one of the most important but under-discussed questions in economics, politics, investing, and national stewardship:

What if GDP is only the income statement, and the real story is hiding on the balance sheet?

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TL;DR Key Takeaways

Roger Ohan began his career in engineering, realized he did not like engineering, earned an MBA, and then entered finance through Chemical Bank, now JPMorgan Chase.

He was placed into a then-obscure corner of the market called fixed income derivatives and became one of the early traders in interest rate swaps, helping build part of what became JPMorgan’s core fixed income business in Europe.

Roger’s worldview was shaped by both extremes of finance: highly liquid, high-volume fixed income markets where billions could move in seconds, and illiquid emerging market equities where assets could trade once a month or once a quarter.

After leaving trading in 1997, he helped build an emerging markets asset management business focused heavily on Russian equities during the privatization boom, including exposure to the extraordinary rise and political destruction surrounding Yukos.

The seed of The Ledger began with a question that bothered him after Hurricane Katrina in 2005: how could a city be destroyed, families lose homes, businesses, memories, and assets, and yet the economic statistics fail to show the destruction of real wealth?

Roger’s core insight is that GDP measures flow, like an income statement, but it does not properly measure the condition of a country’s balance sheet.

His Gross National Assets framework looks at five categories of national assets: natural resources, infrastructure, human capital, intellectual capital, and financial assets.

Those assets must then be weighed against liabilities, including debt, unfunded promises, deteriorating infrastructure, depleted resources, and future obligations.

Over those assets sits what Roger calls the governance multiplier. Good governance compounds national wealth. Bad governance can destroy the same asset base.

The contrast between Norway and Nigeria is central to his framework. Both had oil. Norway converted its natural resources into a financial asset through a sovereign wealth fund and strong governance. Nigeria largely failed to convert its oil wealth into a durable national balance sheet strength.

Nauru is Roger’s cautionary tale. Once one of the richest countries in the world per capita because of phosphate deposits created by ancient bird guano, it mined its balance sheet, spent the proceeds poorly, and collapsed after the resource declined.

Singapore and South Korea are the positive examples. Both began with very little, especially South Korea after the Korean War and Singapore after separation from Malaysia, but built enormous sovereign wealth by investing in human capital, infrastructure, rule of law, and governance.

Cuba is one of Roger’s most striking examples of trapped human capital: a country with literacy, doctors, engineers, and education, but a governance structure that forces talent into low-productivity survival behaviors rather than compounding national wealth.

The framework introduces the “sovereign share,” the value of a country’s net assets divided by its population. In simple terms, it asks: how much national equity does each citizen effectively inherit?

AI complicates the framework because human capital is the largest balance sheet asset in advanced economies. If AI reduces the value of human labor faster than new productive roles emerge, national balance sheets may weaken in ways GDP will not immediately reveal.

Roger’s framework applies to families, business owners, and investors, too. Income matters, but the balance sheet matters more. A high-earning person or nation can still become fragile if they consume everything and fail to compound assets.

The deeper message: nations, businesses, and families should stop confusing activity with wealth creation.

Why You Should Listen

This ATOMIQ LEVEL conversation with Roger Ohan is not just a macroeconomics interview. It is the story of a man who spent decades inside the machinery of global finance, watching markets move in real time, watching countries rise and fall on governance choices, watching assets be created, extracted, wasted, or compounded, and finally deciding that the way we measure national prosperity is dangerously incomplete.

It is about a trader who began in the obscure world of interest rate swaps before they became central to modern finance, then moved into emerging market asset management, Russian equities, infrastructure advisory, fund administration, private equity restructurings, and board-level investment work.

It is about the moment Hurricane Katrina exposed something that GDP could not explain: the destruction of real human, physical, and financial wealth hiding beneath a headline economic metric that could still look superficially fine.

It is about why a car crash, a burned house, a ghost city, an unused bridge, a depleted island, and a mismanaged oil field can all increase measured economic activity while making the owner, the city, the country, or the people poorer.

It is about why Norway became one of the great sovereign wealth stories in modern history while other oil-rich nations burned through their balance sheets.

It is about why Singapore and South Korea prove that human capital, governance, education, rule of law, infrastructure, and patience can turn poor nations into extraordinary compounding machines.

It is about why the AI revolution may force us to rethink the value of human capital on national balance sheets, especially if brains, not just hands, are now being augmented or replaced.

Most of all, this conversation is about truth in accounting. Not the accounting of a company. The accounting of civilization.

Press play on this conversation with Roger Ohan, author of The Ledger, if you want a framework that helps you see through economic gaslighting, political scorekeeping, distorted GDP narratives, and the dangerous habit of confusing spending with wealth creation.

Because a nation can look busy and still be getting poorer.

A business can have revenue and still be eroding its future.

A family can have income and still fail to build a balance sheet.

And once you learn to see the ledger, you never look at prosperity the same way again.

The Man Who Looked Past GDP and Found the Missing Ledger

Gross National Assets and the Balance Sheet of Civilization

Before Roger Ohan wrote The Ledger, before he began developing the Gross National Assets framework, before he started asking whether countries were actually getting richer or merely producing activity that looked like growth, he was an engineer who did not want to be an engineer.

So he did what many smart people do when the first track does not quite fit.

He got an MBA.

Then he walked into finance through a bank called Chemical Bank, which would eventually become JPMorgan Chase. He did not begin in some obvious center of glamour. He was placed into a strange and obscure corner of the market that almost did not exist yet: fixed income derivatives. Interest rate swaps.

At the time, that was not the sprawling, central, institutional market it would later become. It was still emerging, still being built, still not entirely understood by the broader financial world. Roger was early. He was lucky, as he says, but he was also capable enough to understand what luck had handed him.

He became one of the early people trading swaps and helped build part of what became JPMorgan’s core fixed income business in Europe.

That is not a small thing.

It meant sitting in markets where every second mattered. Government bonds, repos, swaps, massive positions, payroll numbers, GDP releases, interest rates, and billions of dollars of exposure moved across screens in real time. A number would hit, and within seconds, markets would respond.

You could win or lose millions before most people even understood what had happened.

That kind of early career leaves a permanent mark. It trains a person to respect flows, liquidity, reflexes, leverage, and the brutal honesty of price. It also teaches a lesson most people outside markets never fully internalize:

The number everyone is watching may not be the number that matters.

The Dumbbell Life of a Market Thinker

Roger’s career did not stay on one side of the financial world. After years in highly liquid fixed income markets, he moved into the opposite environment: emerging market equities.

That shift gave him what he calls a dumbbell background.

On one side, there were some of the most liquid instruments in the world, moving constantly, reacting instantly, and repricing by the second.

On the other side, there were deeply illiquid emerging market securities, including Russian equities, where options might trade once a month or once a quarter.

One world was all speed. The other was all opacity.

Both taught him something.

From fixed income, he learned how the global monetary machine moves. From emerging markets, he learned what happens when governance, property rights, incentives, and state power sit underneath the numbers. He saw assets that looked cheap because they were cheap, and assets that looked cheap because the market did not trust the system around them.

One of the defining examples was Russia in the late 1990s, during the privatization boom. Roger was investing in Russian equities from roughly 1997 to 2000, a period when assets under management could go from zero to $500 million and then back down to $30 million because that was what Russian equities did.

They boomed. They collapsed.

They revealed the balance sheet and the governance structure at the same time.

Yukos and the Lesson of Governance

One of the stories Roger tells is about Yukos, once one of the most valuable oil companies in the world. At the time, the company was being treated like a cash register by its owner, Mikhail Khodorkovsky. Money was being pulled out. The market assigned the company a low value because governance was weak, and outside investors had no reason to trust that the asset base would be treated properly.

Then came a different idea.

Instead of extracting value from the company in the short term, leave the money in. Clean up the accounts. Use IFRS statements. Make the company transparent. Turn it from one of the dirtiest companies in Russia, financially speaking, into one of the cleanest.

The value skyrocketed.

That story matters because it shows one of Roger’s central insights long before he wrote the book. The asset was already there. The oil existed. The company existed. The productive base existed. What changed was governance.

The market did not merely pay for the asset. It paid for the trust in the asset.

Then Khodorkovsky took on Vladimir Putin. Putin decided the company was no longer really his. Khodorkovsky ended up in exile, and the story became another lesson in the same ledger.

Assets do not exist in a vacuum. They exist inside power structures. And when governance breaks, value can disappear.

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The Moment Katrina Broke the Metric

The idea behind The Ledger did not arrive all at once. It accumulated over decades. But one moment crystallized it for Roger: Hurricane Katrina in 2005.

New Orleans was devastated. People died. Families lost homes. Businesses were destroyed. Generations of memories disappeared. Photo albums, which Roger notes may matter even more than the physical structure of a house, were gone. Local wealth, civic wealth, emotional wealth, human wealth, and physical wealth were wiped out.

Then the economic numbers came in. And they did not tell the truth.

That was the problem.

GDP could reflect the rebuilding activity. It could count the spending. It could capture the contractors, materials, repairs, and money changing hands. But it did not properly show the destruction of the balance sheet.

A city could be devastated, and the number could still fail to reveal the real loss.

That bothered Roger. It should bother all of us. Because once you see it in Katrina, you begin to see it everywhere.

The Car Crash That Explains the Economy

Roger uses a simple example to explain the flaw.

Imagine you own a $100,000 car. You crash it. The repair costs $10,000. You pay the mechanic. The mechanic is $10,000 richer. You are $10,000 poorer. Between the two of you, the money moved from one pocket to another.

But GDP records $10,000 of economic activity.

The problem is that your balance sheet is worse. Your cash is down. Your car may still be worth less than it was before the crash, even after the repair. The accident history may impair the value. The asset was damaged, and the repair did not necessarily restore the whole loss.

The economy looks more active. You are poorer. That is the central illusion.

Now scale that up. A house burns down. A hurricane destroys a city. A bridge is built where nobody needs it. A ghost city rises in China and then gets demolished. A country extracts oil or phosphate from the ground and spends the proceeds without replacing the asset.

GDP may count the work. The ledger asks whether wealth was actually created.

GDP Is the Income Statement

Roger is careful not to dismiss GDP entirely. GDP is useful. It was built for a purpose. It emerged during the Depression as a way to measure economic flow, and it became extraordinarily useful during World War II and the Cold War for understanding production capacity and how much of the economy could be shifted toward war, defense, or other priorities.

GDP does what it was designed to do. But it was never meant to do everything. GDP is the income statement. Roger wants us to look at the balance sheet.

That distinction is everything. A company can have revenue and still be fragile. A family can have a large income and still be broke. A country can show growth while destroying the very assets that make future prosperity possible.

Once you understand that, the economic conversation changes. You no longer ask only, “How much activity happened this quarter?”

You ask, “What happened to the asset base?”

Gross National Assets

Roger’s Gross National Assets framework begins with five major categories of assets.

1. The first is natural assets: forests, fisheries, oil, coal, rare earths, minerals, land, water, and the resources embedded in the earth or ecosystem. Some are renewable if managed properly. A forest can be perpetual if replanted and maintained. Oil, once pulled from the ground and burned, is gone.

2. The second is infrastructure: roads, bridges, railways, ports, airports, grids, refineries, hospitals, schools, broadband, and the physical systems that allow an economy to function more efficiently.

3. The third is human capital, which Roger argues is usually the most important asset in a country. People work, build, think, care, create, consume, invent, teach, produce, and govern. The value of a country is often downstream of the capacity of its people.

4. The fourth is intellectual capital: patents, technologies, scientific knowledge, processes, brands, institutional know-how, software, research, and the ideas that make the economy more productive.

5. The fifth is financial assets: cash, reserves, sovereign wealth funds, public financial holdings, and other forms of stored monetary value.

Against these assets sit liabilities.

Debt. Pension promises. Social insurance obligations. Deteriorating bridges. Depleted forests. Extracted oil. Environmental damage. Deferred maintenance. Unfunded future promises. The things we like to ignore until they become impossible to ignore.

Then, over the top of all of this, Roger places the governance multiplier. Good governance multiplies assets. Bad governance destroys them.

Norway, Nigeria, and the Governance Multiplier

The contrast between Norway and Nigeria is one of Roger’s clearest examples. Both had oil. That is the starting point. The natural asset existed in both places. But the outcome was radically different.

Norway created one of the world’s great sovereign wealth funds. It put rules in place before the oil money became irresistible. It designed the fund to be perpetual. It restricted what politicians could do with it. It converted a natural asset, oil in the ground, into a financial asset that could benefit future generations.

The governance framework protected the balance sheet.

Nigeria had enormous oil wealth too, but much of that wealth did not become durable national capital. It did not compound through human development, infrastructure, institutional strength, or broad-based financial assets in the same way. The oil came out of the ground, but the national balance sheet did not strengthen proportionately.

The difference was not the existence of oil. The difference was governance.

That is why Roger’s framework is not merely economic. It is civilizational. It asks whether a country has the institutional discipline to convert temporary resource wealth into permanent national strength.

The Island Made of Money That Became a Prison

Then there is Nauru.

Most people could not find it on a map. Roger says even after writing about it, he would struggle to put his finger within 500 miles of it on a globe. It is a tiny island in the Pacific Ocean, and at one point, it was one of the richest countries in the world per capita.

Why?

Birds.

For millions of years, birds nested there. Their droppings became phosphate deposits, valuable as fertilizer. The island was, in a very literal sense, made of money.

So Nauru mined it. It exported the phosphate. It spent the money. Citizens enjoyed benefits. The country looked rich. GDP looked impressive. But the country was consuming its balance sheet. The asset was being dug out and shipped away.

Then the quality of the phosphate declined. The revenue stopped. The balance sheet was gone.

Today, Nauru survives in part through arrangements such as serving as a detention location for asylum seekers intercepted by Australia.

That is the cautionary tale.

A country can be rich on paper while it is liquidating itself.

Singapore and South Korea: Starting From Nearly Nothing

If Nauru is the warning, Singapore and South Korea are the inspiration.

Singapore began with almost nothing. When it separated from Malaysia, it did not have abundant natural resources or vast land. Its people were poor. Its future was not guaranteed. But the government invested in human capital, rule of law, infrastructure, institutional credibility, and governance.

It made itself a place where people could trust the system. That trust became an asset.

South Korea’s story is equally powerful. After the Korean War, the country was devastated. It had little infrastructure, little financial capital, limited natural resource wealth, and a population that had to be educated and developed over generations. It invested in people, factories, universities, engineers, companies, and national capability.

Today, the world carries Samsung phones and drives Korean cars. That was not an accident. It was the balance sheet construction.

Singapore and South Korea show that a country can begin with very little and still create enormous wealth if it compounds human capital, infrastructure, intellectual capital, and governance over time.

That is the positive side of Roger’s ledger.

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Cuba and the Tragedy of Trapped Human Capital

Cuba becomes one of the most haunting examples because it shows that human capital can exist and still fail to compound.

Roger points out that Cuba has high literacy, a strong base of doctors, a healthcare system with real human skill, and even specialized talent like nuclear engineers. Yet the country remains poor. Why? Because the governance structure does not allow those assets to become fully productive.

A doctor can make more in the tourism economy from tips than from practicing medicine under the official system. Highly educated people are pushed into survival behaviors rather than compounding the value of their education.

That is balance sheet destruction in human form. The asset exists. The system traps it.

This is what makes Roger’s framework so powerful. It does not simply ask whether a country has resources or educated people. It asks whether the system allows those assets to generate durable value.

The Sovereign Share

One of Roger’s most provocative ideas is the “sovereign share.”

Take the gross net assets of a country and divide it by the total population. What you get is a kind of citizen equity value, the implied share of national wealth each person inherits.

It is not a literal brokerage account. It is a way of thinking.

What is each citizen’s stake in the national balance sheet?

Are we passing on more equity to the next generation than we inherited?

Or are we consuming the asset base and calling it growth?

This reframes politics, investing, citizenship, and public finance. It turns arguments about spending, tax cuts, infrastructure, education, resource extraction, healthcare, and deficits into balance sheet questions.

Will this decision increase the sovereign share?

Will it reduce it?

Will it compound the next generation’s inheritance?

Or will it leave them with more liabilities and fewer assets?

That is a better question than whether this quarter’s GDP looked good.

AI and the Balance Sheet Shock

The conversation then moves into AI, where Roger’s framework becomes even more urgent. In most advanced economies, human capital is the largest asset on the national balance sheet. People’s knowledge, skills, productivity, creativity, and labor capacity drive enormous value. But AI creates a new uncertainty.

If intelligence becomes abundant, what happens to the value of certain forms of human capital?

Roger is careful here. In prior technological revolutions, jobs changed, but total employment often adapted over time. New roles emerged. Humans moved from hands to machines, from fields to factories, from factories to services, from routine labor to knowledge work.

But AI may be different because it moves into the cognitive layer. The machine is not merely replacing muscle. It is beginning to augment or replace parts of the brain.

If new, productive work emerges fast enough, human capital may adapt again. If not, the value of human capital on national balance sheets could shrink. That would be a profound economic, social, and political event.

And GDP may not warn us early enough.

That is why a balance sheet framework matters. It can help us ask not just whether AI companies are growing, but what AI is doing to the value of human capability across the broader economy.

The Governance Question Becomes Everything

Chris makes an observation in the conversation that brings the whole framework into focus. Every place has some natural resources or potential resources. Every place has some infrastructure or the possibility of building it. Every place has people. Intellectual capital is now being democratized through AI in ways that were unimaginable just a few years ago.

So what becomes the linchpin?

Governance.

Roger agrees.

If governance squanders the other assets, it does not matter how rich the natural resource base is. It does not matter how educated the population is. It does not matter how much infrastructure gets built. It does not matter how many patents exist or how much money flows through the system.

Bad governance can eat the balance sheet. Good governance can compound it. That applies to countries, states, cities, businesses, and families.

It is not partisan. It is structural.

Do the rules protect compounding?

Do leaders steward assets for the future?

Can temporary wealth be converted into permanent capital?

Can human capital be developed and deployed productively?

Can infrastructure be maintained rather than merely announced?

Can natural resources be converted into enduring assets rather than consumed and forgotten?

Those are the governance questions that matter.

The Ledger for Families and Business Owners

Near the end of the conversation, Roger brings the framework home.

Anyone who has built or sold a business intuitively understands the difference between the income statement and balance sheet. Revenue matters. Profit matters. Cash flow matters. But the real value is in what compounds.

If a business earns a lot and spends everything, it may look successful but fail to build enterprise value. If a family earns a lot and consumes everything, it may enjoy a high-status lifestyle but remain fragile. If a country produces activity but destroys its natural assets, underinvests in people, depletes infrastructure, and piles up liabilities, it may look prosperous while weakening.

This is why the framework is not only for macro nerds. It is for anyone who wants to preserve and grow wealth. Your personal income statement is what you earn and spend.

Your balance sheet is what remains, what compounds, what protects you, and what gives future options to the people you love.

Roger’s final point is human. Health may be the most important asset of all. In the United States, even a family with several million dollars of net worth can face devastation from a severe medical event. In other countries, that same risk may be structurally different. Asset protection depends on what the asset is, where it sits, and what system surrounds it.

That is the ledger again.

Not just money.

Assets, liabilities, governance, and fragility.

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Closing Thought

This ATOMIQ LEVEL conversation with Roger Ohan is a rare kind of macro conversation because it does not get trapped in the usual debate about whether GDP is up, inflation is down, markets are strong, or politicians are winning.

It asks a more fundamental question.

Are we actually getting wealthier?

Roger’s answer is that we cannot know unless we look at the balance sheet. We need to know what is happening to natural assets, infrastructure, human capital, intellectual capital, financial assets, liabilities, and governance. We need to know whether we are compounding value or merely generating activity. We need to know whether the sovereign share is rising or falling.

For investors, this is a framework for seeing through headline noise.

For business owners, it is a reminder that cash flow without compounding can still lead to fragility.

For families, it is a reminder that high income is not the same thing as durable wealth.

For citizens, it is a reminder that the promises made in your name are liabilities on someone’s balance sheet.

And for leaders, it is a reminder that stewardship is not measured by how much activity you create today.

It is measured by what remains tomorrow.

Press play on this episode with Roger Ohan, if you want to understand why GDP alone is not enough, why governance may be the ultimate multiplier, and why the real wealth of a nation, a business, or a family lives on the balance sheet.

Because the income statement tells you what happened. The ledger tells you what (and who) survives.

The real risk is doing nothing!

~Chris J Snook

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Connect with AI Colorado and Robert Reich

Before you read the show notes below, connect with AI Colorado and Robert Reich at

https://www.aicolorado.org

AI Colorado is being built as a community intelligence layer for one of the most urgent questions of our time:

How do humans stay informed, connected, useful, creative, and locally empowered in a world where artificial intelligence is evolving faster than any institution can comfortably absorb?

Robert’s work sits at the intersection of startups, community building, human agency, local ecosystems, AI literacy, and the belief that the best way to navigate technological overwhelm is not to isolate, panic, or wait for permission.

It is to gather.

It is to learn.

It is to help each other move.

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TL;DR Key Takeaways

Robert Reich is a serial entrepreneur who moved from New York to Colorado in 2006 after school in Georgia and early time back in New York. He describes himself as an introvert-extrovert who likes solving problems at a machine, then turning those solutions into companies.

One of Robert’s personal rituals as an entrepreneur is making skateboards for the companies he starts. Some succeed. Some fail. He keeps the boards intact because they are not just artifacts for the wall. They are meant to be ridden.

Robert and Chris first crossed paths in the Colorado startup ecosystem around 2013 to 2015, during a period when the state’s “give first” culture was becoming a defining feature of its entrepreneurial identity.

Colorado’s startup ecosystem became a powerful example of how communities of common interest can accelerate people, ideas, companies, and confidence without needing a centralized gatekeeper.

Robert helped build and grow the Boulder/Denver New Tech ecosystem, including community maps and events that made it easier for founders, mentors, service providers, and builders to find each other.

Chris credits Robert’s ecosystem mapping work with helping him see the opportunity to light up Fort Collins and connect northern Colorado into the broader startup network.

A major theme of the conversation is that Colorado’s unique advantage was never just technology. It was culture: people who were willing to show up, ask useful questions, give first, mentor, connect dots, and create access without hoarding status.

AI Colorado is Robert’s attempt to bring that same community intelligence into the age of artificial intelligence.

The platform begins with a map of the state and an algorithm designed to connect people based on their interests, sectors, counties, topics, and skill levels.

AI Colorado is not simply a vendor directory. It is designed to help people understand how they are connected, what they should learn next, who they should meet, what events they should attend, and how they can become more competitive in an AI-shaped economy.

The conversation frames AI anxiety as different from prior technology waves because this shift is horizontal. It is not disrupting one industry at a time. It is touching hundreds of workflows, roles, and professions at once.

Robert and Chris argue that the most profound difference is that AI is no longer merely helping humans perform work. It is beginning to define, execute, and route work inside the black box without the human always remaining at the top of the stack.

The practical advice for listeners is to start small, personal, and concrete. Use paid AI tools if possible. Give them real context. Ask them to summarize, critique, explain, compare, or help with something you already understand well enough to validate.

Robert emphasizes that anxiety can become confidence once people experience AI saving them time on something personal and useful.

The deeper message: the future may belong less to the person who tries to keep up alone and more to the community that learns how to help its members keep moving together.

Why You Should Listen

This ATOMIQ LEVEL conversation with Robert Reich is not just an AI interview. It is a reunion between two builders who met inside Colorado’s startup ecosystem at a time when “give first” was more than a slogan and community was still one of the most powerful technologies in the room.

It is about a serial entrepreneur who used skateboards as company artifacts, helped build New Tech community gatherings, mapped local startup activity, and then looked at the AI wave and realized something familiar was needed again.

A map. A gathering point. A way for people to find each other before the complexity swallowed them.

It is about why AI Colorado is not simply another AI website, tool, directory, or newsletter. It is an attempt to turn local community into an adaptive intelligence system, one that can meet beginners, experts, founders, workers, business owners, public leaders, and curious citizens where they are and help them take the next step.

It is about anxiety, but not despair. Robert and Chris do not pretend the AI transition is small. They do not pretend governments, corporations, schools, or institutions are prepared to move at the speed of the change. They do not pretend that everyone can calmly plan five years ahead when the tools themselves are changing every week.

But they also do not surrender to panic. They return to human agency. They return to local trust.

They return to the Colorado lesson: people who show up, contribute, ask better questions, and help each other can move faster than people waiting for top-down permission.

Most of all, this conversation is about the human premium in the agentic age.

When machines can execute, optimize, respond, and even define work, the next arbitrage may not be speed.

It may be trust. It may be community.

It may be a human being who knows enough to connect two other human beings at exactly the right time.

Press play on this conversation with Robert Reich of AI Colorado if you want to understand why the next chapter of AI literacy may not start in a corporate boardroom or federal policy memo.

It may start in a local ecosystem willing to help its people get less afraid and more capable, one useful connection at a time.

Because the future is arriving too fast to navigate alone.

The Man Mapping Human Agency in the Age of AI

Before Robert Reich became the chief instigator and self-described bottle washer behind AI Colorado, before he began building a platform to help people across a state understand, learn, connect, and compete in the age of artificial intelligence, he was already the kind of founder who liked to turn a company into something you could ride.

Literally.

When Robert starts companies, he often makes skateboards for them. Not decorative skateboards meant only for a wall, but boards that can actually be ridden. Some of the companies work. Some do not. Some become exits. Some become lessons. But the boards stay intact.

There is something revealing in that detail.

Robert does not treat entrepreneurship as a trophy case. He treats it as motion. A company is something you build, test, ride, fall off of, repair, learn from, and maybe ride again. The blood, when it shows up, is usually not from the company failing. It is from somebody riding the board.

That feels like the right place to begin, because this conversation is not really about AI as software.

It is about movement. How communities move. How humans move. How people keep moving when the map is changing beneath their feet.

Robert was born in New York, went to school in Georgia, returned to New York, and then moved to Colorado in 2006. By his own description, he is a classic serial entrepreneur and an introvert-extrovert, someone who may not naturally work the room at a barbecue, but who loves sitting in front of a machine, solving problems, and turning useful solutions into something larger.

That profile matters because Robert’s work has always lived between the machine and the community.

He likes to build things. But he also knows that technology without humans around it does not become culture.

The Colorado Way

Chris and Robert first crossed paths years ago inside the Colorado startup ecosystem, roughly between 2013 and 2015, when Chris had moved from Southern California to Colorado with a young family and no clear plan except the instinct that something different might be waiting there.

It was.

Colorado had something that is hard to manufacture and easy to underestimate until you experience it.

Give first.

The phrase has become familiar in startup circles, but in Colorado it was not just a brand line. It was a social operating system. People showed up. People helped. People mentored. People with real money, real exits, real scar tissue, and real responsibilities still spent hours on a Thursday night listening to someone with a napkin-stage idea and asking the kind of questions that could move them forward.

Chris had been around startup ecosystems before. Southern California had activity. Puerto Rico had talent and drive. Arizona had activity and grit. San Francisco had density. But Colorado had a specific kind of generosity that felt different.

Robert tells a small story that explains it better than any ecosystem report could. When he first moved to Colorado, he went to the Whole Foods on Pearl Street looking for cream cheese. In New York, maybe someone points toward aisle five, if they respond at all. In Boulder, the person did not merely point. They physically walked him there.

That was his indoctrination into the culture.

Not “go over there.”

“Come with me.”

That difference became the soul of the ecosystem.

From Bagels to New Tech

Robert’s entry into Colorado’s startup community began the way many meaningful things begin: with a need to meet people.

He was new. He did not know the ecosystem. He was working on something interesting and wanted to find others. So he borrowed inspiration from an event he had seen in New York and helped host an early New Tech gathering in his office. He brought bagels. People came. Not a few people.

Dozens. Then more.

Between Robert’s early network, people like Brad Feld, David Cohen, and others inviting founders, investors, mentors, and builders, the event became a gathering point. At one stage, hundreds of people a month were showing up in Boulder.

The gathering was not just about pitch practice or demo nights. It became a gateway. A person could show up, learn what was happening, ask questions, meet people, and plug into the community. Over time, the New Tech energy spread and evolved across Boulder, Denver, Fort Collins, and other nodes in the state.

What made it work was not just attendance.

It was agency.

People did not have to be the ultimate expert to contribute. They could ask one useful question. They could mentor on one thing they had already done. They could help a founder avoid one mistake. They could make one introduction. They could volunteer at one event. They could become part of the network before they had earned some official credential from the old power structure.

That is how real ecosystems compound. Not through perfect central planning. Through many people doing useful things without needing to own the whole thing.

The Map That Lit Up a Region

One of Robert’s early contributions was a map of the Colorado startup ecosystem. The site let companies, founders, service providers, and startup-related organizations register themselves by geography. To an outsider, it might have looked like a simple directory or visualization.

To Chris, it became something more.

When he looked at the map from Fort Collins, he saw the absence. He had already met real founders, builders, CSU people, Innosphere people, small business operators, tech builders, service providers, and community leaders. They were alive in the real world, but missing from the digital map.

That gap became a mission.

Chris began lighting up Fort Collins on Robert’s map, not because someone had assigned him to do it, but because the tool made the invisible visible. Once people could see themselves in the ecosystem, they could connect. Once they connected, they could help. Once they helped, the community could grow beyond the familiar Boulder-Denver corridor.

That is the power of maps. They do not create the terrain. They reveal where people can move.

In that sense, Robert’s old startup map becomes the spiritual ancestor of AI Colorado. The technology has changed. The stakes have changed. The speed has changed. But the underlying question remains:

How do people find each other when the system is too complex for any one person to understand alone?

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The AI Wave Is Not Like the Last Wave

From there, the conversation moves into the present, where the technological shift is no longer about mapping startups or building community around early-stage companies.

It is about artificial intelligence. And the tone changes.

Not into panic, exactly, but into urgency. Robert and Chris both recognize that this wave is different. The internet changed distribution. Napster disrupted music. The read-write web disrupted media and publishing. The iPhone changed mobility, behavior, and interface design. Cloud software reshaped companies. Blockchain and crypto created new coordination and settlement models.

But AI is horizontal.

That is the word that matters.

It is not coming for one industry at a time. It is affecting legal, finance, software, marketing, education, healthcare, media, accounting, operations, customer service, research, administration, government, and entrepreneurship simultaneously. It touches workflows everywhere because language, logic, summarization, classification, analysis, code, communication, and decision support are everywhere.

That is why the anxiety feels different. A prior wave might disrupt a sector. This one challenges the structure of work itself.

For most of human history, even when machines replaced physical labor, humans still defined the work. We decided what needed doing, organized the labor, deployed the tools, and interpreted the results. Machines increased leverage. They made work faster, cheaper, stronger, and more scalable.

But now the machine can begin to define the work too. That is the psychological break.

When the Human Moves Inside the Black Box

Robert explains the shift through a simple mental model. In the old technology stack, the human sat at the top. Software moved information from one place to another. An email came in. A person read it. A person wrote the response. The system routed it onward. The person was outside the black box, interacting with it.

AI changes that.

Now the role the human used to play can move inside the system. The email can be read, interpreted, drafted, routed, and sent without ever fully leaving the black box. Whether or not we want that to happen in every case is a separate question. The capability exists.

That is why this moment feels so unsettling. It is not merely that a machine can help us work faster. It is that the system can begin to perform parts of our judgment loop.

For some people, that is thrilling. For others, it is terrifying.

For most, it is both.

And because the technology is improving so quickly, the old comfort of waiting no longer works. The tool you tested yesterday may be meaningfully worse than the tool available tomorrow. The clunky output you dismissed last month may already be obsolete. The bad demo that made someone laugh may become production-grade before the procurement committee finishes debating whether to start a pilot.

The worst AI will ever be is often the version you are using today.

That sentence creates anxiety. It also creates opportunity.

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Anxiety, Excitement, and the Missing Safe Harbor

Chris names the emotional center of the transition clearly. Humans feel worry, doubt, and anxiety. Machines do not. But humans also feel excitement, inspiration, and wonder. The same force that terrifies one person can energize another.

The trouble right now is that many people feel forced to change before they have decided they want the change.

That matters.

Human beings resist being changed. We do not always resist change when we choose it. The psychological difference is enormous. When someone chooses to learn, build, explore, and adapt, the unknown can become adventure. When change feels imposed, the same unknown becomes a threat.

AI, for many people, feels imposed.

There is no obvious safe harbor yet. Government is too slow by design. Large institutions are not built to respond to exponential complexity. Corporations can adopt tools, but often struggle to change culture. Schools are lagging. Families are overwhelmed. Small businesses are busy surviving. Professionals are not sure whether to be curious, defensive, or both.

And because the AI race is global, no single local authority can simply slow the whole thing down. Freedom-oriented nations, authoritarian nations, open-source communities, frontier labs, startups, and individual builders are all operating inside the same accelerating landscape.

Slowing down may not be possible. Calming down is. That is where community becomes strategy.

Why AI Colorado Exists

Robert started AI Colorado because he believes Colorado has the right cultural DNA for this moment. The state has a long history of people willing to help each other learn, build, experiment, and connect. The old startup ecosystem taught him that if people know where to go, who to meet, what to ask, and how to contribute, they can become more capable faster.

AI Colorado is built around that insight.

It begins with a map of the state. But unlike a simple directory, it is not just trying to list vendors. It is trying to show how people are connected to each other based on their interests, skills, geography, sectors, and needs. The goal is not merely to answer, “Who is doing AI?”

The goal is to answer, “Who should you learn from, connect with, help, or meet next?”

That is a different kind of map. It is not static. It is relational.

Robert describes an algorithm at the center of the platform, designed to create more relevant connections, learning paths, briefs, and recommendations. A user signs up, identifies a county, sector, topics of interest, and skill level. From there, AI Colorado begins personalizing a journey. It can recommend lessons, articles, people, events, and daily briefs based on where the person actually is in their AI journey.

If someone is a beginner, it speaks to them like a beginner. If someone is an expert, it treats them like an expert.

That may sound obvious, but it is exactly what most AI education efforts miss. People are not anxious only because AI is powerful. They are anxious because they do not know where they fit. They do not know which explanation is for them. They do not know what to ignore. They do not know whether they are behind, ahead, or completely asking the wrong question.

AI Colorado is trying to create orientation. And orientation is a form of relief.

From Vendor Directory to Community Intelligence

The important thing about AI Colorado is that it is not just a marketplace. Robert does not frame it as a list of AI consultants or tools. He frames it as software that helps a community become more competitive.

That distinction matters. A vendor directory asks, “Who can sell me something?”

A community intelligence system asks, “How do we collectively get smarter?”

That is why the platform includes daily briefs, personalized lessons, connection recommendations, topic tracking, and the possibility of scaling to other states once the Colorado model works. Robert’s current focus is Colorado because a system needs a segment where it can prove itself. But the architecture could eventually support other regions, with new domains, skins, and local leadership.

Nail it, then scale it.

That is the old startup rule. Applied to civic AI literacy.

The Human Network as the Last Mile

One of the more powerful ideas in the conversation is that AI Colorado is trying to encode something Robert and Chris both experienced in the Colorado startup community: the human connector.

Every ecosystem has a few people who seem to know who should meet whom. They remember what someone is building. They know who solved a similar problem. They can say, “You should talk to her,” or “You need to go to this event,” or “That person is two steps ahead of you on the exact issue you are facing.”

Those people are incredibly valuable. They are also scarce.

AI Colorado is trying to create software that can perform part of that role, not by replacing humans, but by helping more people experience the benefit of intelligent connection. It cannot fully replicate the intuition of a great networker, but it can surface possibilities that would otherwise stay hidden.

That is the human network as the last mile. AI can help route. Humans still create trust.

How to Start Without Getting Overwhelmed

For listeners who are not deep in AI, Robert’s practical guidance is refreshingly simple: start with something you already understand.

Do not begin by asking AI to solve a problem in a domain where you cannot judge the answer. Do not type three vague words like you are searching Google and then dismiss the tool because the answer is shallow. Do not paste private or sensitive information into a model without thinking. Do not expect magic from zero context.

Give it something to chew on.

Take an email, article, contract, terms of service, ticket, document, outline, spreadsheet, or piece of writing and ask it to summarize, critique, explain, compare, or ask clarifying questions. Use something personal enough to matter, but not sensitive enough to create unnecessary risk.

Ask it what you are missing.

Ask it to explain what something means.

Ask it what questions you should be asking.

Ask it to critique your thinking.

Treat it less like a search engine and more like a patient thought partner.

The point is not to become an AI expert on day one. The point is to have one useful experience that reduces fear and creates curiosity. Once a person sees AI save them an hour, clarify a confusing document, improve a piece of writing, or help them understand a process, anxiety begins to turn into confidence.

That is the doorway.

The Perfect Time to Be Curious

Chris offers a phrase that captures the moment: it is the perfect time to be dumb.

Robert softens it: be curious.

Both are pointing to the same truth. In this era, not knowing can become an advantage if you are willing to ask better questions. You do not need to pretend you understand GitHub, agents, context windows, model routing, MCP, vector databases, or inference costs before you begin. You can simply tell the tool what you do not know and ask what questions to ask next.

That is a profound shift.

For decades, expertise often required knowing the jargon before you could enter the room. Now, natural language gives more people a way in. A small business owner can say, “I run an HVAC company. I do not know how local search works. I cannot afford a $10,000-a-month agency. What should I do first?” And the tool can begin scaffolding a plan.

That does not make the business owner an SEO expert overnight. But it may help them ask better questions of an agency. It may help them avoid being overcharged. It may help them identify one practical improvement. It may help them become more capable.

That is agency. Not AI replacing the human.

AI is expanding what the human can understand and attempt.

The New Anxiety of Efficiency

The conversation also surfaces a more subtle anxiety. Once AI makes someone ten times more efficient at a task, they may suddenly wonder whether they should become ten times more efficient at everything.

That is a trap.

The promise of AI is often sold as time savings, but humans do not automatically convert saved time into peace. We often convert it into more ambition, more projects, more output, more comparison, and more pressure.

The inbox agent may save time, but then the mind fills that time with a new objective. The writing assistant may speed up content, but then the creator starts producing five times more and feels behind anyway. The automation may remove one bottleneck, but reveal three more.

The race can become self-imposed.

That is why communities matter. They help people calibrate. They provide mirrors, boundaries, shared stories, and reminders that the point of becoming more capable is not to become more frantic.

The goal is not simply speed. The goal is better human choices.

The Next Arbitrage May Be Human

Near the end of the conversation, Chris and Robert explore a striking idea. In a world where agents can arbitrage prediction markets, generate code, summarize documents, and operate faster than humans, the easy arbitrage will disappear quickly. Anything purely informational, purely computational, or purely speed-based may get competed away.

So where does durable advantage remain?

Maybe in the things that take time.

Maybe in trust.

Maybe in relationships.

Maybe in community.

Maybe in human agency, empathy, connection, and local credibility.

That does not mean technology becomes irrelevant. It means the human layer becomes more precious precisely because the technical layer accelerates. When machines can produce infinite output, people will value the signals that help them decide what deserves attention, trust, and action.

A good community becomes a filter.

A trusted human becomes a guide.

A local ecosystem becomes a resilience layer.

That is the deeper promise of AI Colorado.

It is not simply helping people use tools.

It is helping people remain oriented inside a world of too many tools.

The Platform That Could Become a Pattern

Robert is clear that AI Colorado is starting in Colorado because it needs a place to prove the model. Over the next year, he believes the team will learn whether a platform dedicated to local AI education, connection, and community competitiveness can work.

If it does, the architecture could be adapted elsewhere. AI California. AI Arizona. AI Texas. AI New York. Each with its own skin, local leadership, local map, local topics, and local relationships.

But Robert is not rushing that. The algorithm needs to work. The connection logic needs to work. The support system needs to work. The human layer needs to stay intact.

That is the paradox. The platform has to use AI. But it cannot become inhuman.

If it is going to help people navigate AI, it has to model the thing it claims to protect: human-centered usefulness.

Closing Thought

This ATOMIQ LEVEL conversation with Robert Reich is a reminder that the AI future will not be solved only by frontier labs, policy makers, venture capitalists, or billion-dollar enterprise platforms.

It will also be shaped by local communities.

By people who ask better questions.

By builders who create maps.

By mentors who show up.

By founders who keep riding the board whether the last company worked or not. By citizens who decide that anxiety is real, but paralysis is optional.

AI Colorado is young, but the idea underneath it is old and proven. Humans learn better together. Ecosystems compound when people give first. Communities become stronger when access expands. Technology becomes more humane when it is grounded in real relationships.

For founders, this episode is a reminder that the next company may not start with a pitch deck. It may start with a problem you personally feel and a community that helps you test it.

For business owners, it is a reminder that AI does not need to be abstract. Start with the work you do every day. Give the tool context. Ask better questions. Build confidence one useful interaction at a time.

For advisors, investors, and leaders, it is a reminder that the people you serve are already feeling the anxiety of this shift, even when they cannot name it.

For communities, it is a reminder that the best response to overwhelming complexity may be the oldest one:

Gather the humans. Map the terrain. Share what works. Help the next person move.

Press play on this episode with Robert Reich of AI Colorado, and you will hear a conversation that begins with old friends, startup memories, skateboards, bagels, and Colorado’s give-first culture, but ends at one of the biggest questions of the agentic age.

How do we make sure the future still has humans at the center?

Because AI may change the work. But humans still have to decide what the work is for.

The real risk is doing nothing!

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Connect with Shawn Glogowski

Before you watch, listen, or read the show article below, connect with Shawn Glogowski, principal and co-founder of Note Advisors.

You can learn more about Shawn and the Note Advisors team here: https://www.noteadvisor.com/team/shawn-glogowski-bio/

Shawn represents a new, and in many ways older, version of wealth advice: fiduciary, human, local in values but national in reach, deeply technical but emotionally intelligent, and built around the idea that the future of financial planning will not be won by the advisor with the flashiest portfolio model.

It will be won by the advisor who can help another human being act on the advice that actually matters.

TL;DR Key Takeaways

Shawn Glogowski did not enter college on a clear financial services path. He grew up in Buffalo, New York, went to school there, and says he “fell into” the financial services profession in 2005 through a family friend.

He began inside a bank-owned broker-dealer environment with proprietary products, sales pressure, high turnover, and the old-school “smile and dial” culture of call nights, desk phones, and learning how to survive by making human connections.

Instead of becoming disillusioned, Shawn found something he loved: being in service to other human beings. That became the thread that carried him through nearly two decades in the profession.

Early in his career, he gravitated toward holistic financial planning rather than product sales. He loved understanding the ripple effects of decisions across investments, insurance, taxes, retirement, estate planning, cash flow, and family life.

A pivotal moment came during his CFP coursework, when another young advisor named Sean introduced him to the idea of a fee-only RIA. Shawn had never heard of that model before, but the conversation stayed with him.

He met his future partner, Tom, in the broker-dealer world. Tom was older and beginning to think about succession, while Shawn was younger and thinking about the kind of firm he wanted to build for the next 30 years.

In 2014, Shawn and Tom broke away, dropped securities licenses, eventually moved away from insurance licensing, and built what became Note Advisors as an independent, fee-only, SEC-registered investment advisory firm.

The move was not only about compensation. It was about escaping the “cage” of broker-dealer compliance and product constraints so they could serve clients the way they believed clients actually needed to be served.

Note Advisors is built around a team model rather than a lone-advisor model. The firm focuses on holistic wealth management, planning, client experience, and the ability to serve clients across multiple dimensions of life.

A major differentiator is the firm’s use of a wealth coach, Christine, who helps bridge the gap between technical financial advice and the client’s relationship with money.

Shawn believes the future of advice is not fee compression as much as value expansion. Advisors who only charge to manage a portfolio may be vulnerable. Advisors who help clients navigate the human, emotional, behavioral, and multigenerational side of wealth may become more valuable.

The firm organizes planning around six pillars: cash flow, insurance, taxes and tax planning, investments, retirement planning, and estate planning, wrapped inside the client’s relationship with money.

AI is not something Shawn fears. He sees it as a productivity tool that can make technical people more efficient and give front-facing advisors more time to be proactive, human, and present with clients.

Shawn believes the future belongs to advisors and firms that use technology as table stakes while differentiating through human connection, empathy, clarity, proactive communication, and trust.

The deeper message: wealth advice is not just about getting the numbers right. It is about helping people actually live the life the numbers say they can afford.

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Why You Should Listen

This ATOMIQ LEVEL conversation with Shawn Glogowski is not just an advisor interview. It is a story about a Buffalo-based fiduciary who came up through the old broker-dealer world, survived the smile-and-dial era, discovered the deeper calling of holistic planning, broke out of the product cage, and built Note Advisors around the belief that the future of wealth advice is profoundly human.

It is about a young advisor who entered the business in 2005 without a grand plan, learned to make calls on Monday nights, chased appointments from phone books and referral lists, and slowly realized that what he loved was not selling financial products.

He loved helping people.

It is about why technical advice is only the beginning. A spreadsheet may say a client can retire at 62, but if that client gets to 62 and cannot emotionally imagine who they are without work, the plan is not complete. The math was right, but the human system was unfinished.

It is about why AI may make the best advisors better and expose the ones who were only hiding behind investment management, generic portfolios, and old distribution advantages.

It is about why the next generation of advisory firms may need more than quants, model portfolios, and financial planning software. They may need wealth coaches. They may need emotional intelligence. They may need multigenerational teams. They may need the courage to talk about money, identity, fear, marriage, children, work, legacy, and what happens after the client achieves the number they thought would make them free.

Most of all, this is a conversation about the difference between delivering advice and helping someone act on it.

That difference is everything.

Press play on this conversation with Shawn Glogowski of Note Advisors if you want to understand where fiduciary advice is heading, why the human advisor is not going away, and why the future of wealth management may depend less on managing money and more on understanding what money means inside a human life.

Because the next era of wealth advice will not be won by the advisor who simply has the best answer.

It will be won by the advisor who can help the client become ready to live it.

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The Advisor Who Escaped the Cage

Before Shawn Glogowski became principal and co-founder of Note Advisors, before he helped build an SEC-registered independent advisory firm, before he was speaking fluently about wealth coaching, relationship with money, value expansion, succession, AI, client experience, and the emotional architecture of financial planning, he was a young man in Buffalo who had stumbled into financial services almost by accident.

That is how he tells it.

He grew up in Western New York. Born and raised in the Buffalo area. Went to school there. Went to college there. He was not on some perfectly charted finance track. There was no cinematic moment where a young Shawn looked at a stock quote and decided, with total clarity, that he would one day become a fiduciary wealth advisor.

The profession found him sideways.

Through a family friend, he ended up inside a bank-owned broker-dealer environment in 2005. Proprietary products. Securities licenses. Insurance products. The old financial services machine. He was in his early twenties, and like so many people who entered that world, he was thrown into a culture where the attrition rate was brutal.

Most people did not survive it. Shawn did.

Not because he loved the product machine. Not because he wanted to become a financial salesperson in the old sense. Something else happened. Beneath the call nights, the proprietary products, the pressure, and the grind, he found the part of the business that lit him up.

He loved being in service to other human beings.

That sentence sounds simple. In his case, it became the foundation for everything that followed.

The Old World of Smile and Dial

The financial services world Shawn entered in 2005 still carried the echoes of an earlier Wall Street sales culture. The desk phone mattered. The call list mattered. The Monday night call session mattered. How many dials? How many touches? How many nos? How many appointments?

This was not the world of polished LinkedIn content, AI-generated newsletters, automated lead funnels, podcast appearances, content engines, and digital credibility. This was still a world where a young advisor learned how to survive by picking up the phone and asking for time.

Shawn remembers those nights. The lists. The teacher’s directory from his wife’s school. The names from his father’s manufacturing company. The feeling that if he could just get one or two people to say yes to a meeting, he might have enough oxygen to keep going.

There was something hard about that world. There was also something useful in it.

It taught rejection. It taught persistence. It taught that financial advice, before it is anything else, is a human contact sport. You had to reach another person. You had to earn a conversation. You had to sit in front of them and explain why they should trust you.

You had to learn how to connect.

That kind of training is unfashionable now, but not irrelevant. In fact, as Shawn and Chris explore in the conversation, one of the dangers of the modern advisory profession is that many young advisors now enter with far better technical training, but far less experience in the human grit of building relationships from scratch.

They may know more planning software. They may know more tax strategies. They may even be better prepared to sit for the CFP. But they may not yet know what it feels like to need one more human being to say yes.

That matters because wealth advice is still built on trust. And trust is not downloaded.

It is earned.

The Planner Inside the Product World

Although Shawn started in the broker-dealer world, he did not fall in love with the product side of the business. He became drawn to planning.

The planning was what made sense to him. Not just selling an investment. Not just recommending insurance. Not just pushing whatever the proprietary product shelf offered. He wanted to understand the whole person and the ripple effects of their decisions.

What happens if this client retires early?

What does that do to cash flow?

What does it do to taxes?

What does it mean for insurance?

What does it mean for estate planning?

What does it mean for the spouse who sees money differently?

What does it mean for the children who may inherit not only wealth, but habits, silence, fear, confusion, or opportunity?

That holistic instinct became a quiet rebellion inside a product-driven environment. Shawn was not alone. He met his partner, Tom, in that broker-dealer world. Tom came from an older generation and had deeper roots in insurance. Shawn was younger and finishing his CFP. Tom was already thinking about succession. Shawn was thinking about the next thirty years of his career.

Together, they began to see the same problem from different sides.

They were trying to operate like fiduciaries inside a structure that was not built to make that easy.

The Conversation That Changed the Map

One of the pivotal moments in Shawn’s story came during his CFP coursework. He met another young advisor, also named Sean, who worked at a fee-only RIA.

Shawn had never heard of that before.

That detail is easy to miss, but it says everything about the era. Today, the language of fiduciary, RIA, fee-only, planning-first advice is far more mainstream. Back then, for someone inside the broker-dealer world, it could feel almost like discovering a hidden door in the same building.

Wait.

You can do this without selling products?

You can be paid for advice?

You can build a firm that is not tethered to a broker-dealer?

You can serve the client without the same product machinery sitting between the advisor and the recommendation?

The conversation stayed with him. It did not immediately create a grand plan, but it planted a seed. Over time, that seed grew into conviction. Shawn wanted to build in that direction. He wanted independence. He wanted to serve clients without being trapped inside a compliance and product cage that increasingly felt misaligned with the work he believed mattered.

There are moments in a career that look small when they happen and enormous in hindsight. That conversation was one of them.

The Cage

Shawn does not describe the broker-dealer transition as a simple moral binary. He is careful about that. He still has friends in the broker-dealer world. There are good people there. The point is not that every person in that model is bad or every independent firm is automatically good.

The point is fit. For Shawn and Tom, the cage became too small.

They were already doing fee-based planning and investment work. They were already trying to operate in a client-centered way. But the more they tried to deliver advice the way they believed clients needed it, the more they ran into walls.

A word in a marketing video could trigger a compliance rejection. A planning tool could not be used the same way another RIA could use it. A communication that might help a client understand a concept could be blocked because of firm liability concerns. The structure existed to protect the institution, but sometimes it prevented the advisor from serving the human being in front of them.

That is when Shawn began to understand the difference between compliance that protects the client and compliance that protects the machine.

He kept hitting his head against the top of the cage. Eventually, he told Tom they had to leave it together, or he was out.

The Breakaway

In 2014, they broke away. They dropped securities licenses and went independent and fee-only. Over time, they moved away from insurance licensing as well. The firm eventually became Note Advisors in its current form: an SEC-registered investment advisory firm built around holistic wealth management and consulting.

It was not easy.

Independence creates freedom, but it also creates responsibility. The broker-dealer cage may restrict you, but it also holds up parts of the roof. Once you leave, you own more of everything: compliance, HR, benefits, technology, client communications, operations, liability, cybersecurity, business development, succession, training, culture, and the emotional weight of building something that has to work.

Shawn would not trade it.

He says if he could do it differently, he would have started the transition earlier.

That is an important line. It is easy for advisors to romanticize independence from the outside. It is also easy to fear it from the inside. Shawn’s answer lives in the middle. Yes, independence is harder. Yes, it creates more complexity. Yes, it demands an entrepreneurial mindset. But for the kind of advisor who wants to build around the client experience and make long-term decisions without institutional drag, it can also become the only honest path.

Note Advisors was built on that bet.

From Lone Advisor to Building a Team

One of the most important shifts Shawn describes is cultural. In the broker-dealer world, advisors may technically share a brand or office, but they often operate as individual competitors. Same business card. Same parent company. Different books. Different incentives. Quiet competition.

Note Advisors is different by design.

The firm is built around a team. One advisor may be the lead relationship, but the client is backed by a broader group. That matters because complex wealth cannot be served well by one heroic generalist forever. Clients have different needs. Families have different dynamics. Younger generations communicate differently. Business owners need different guidance than retirees. Technical planning requires different skills than emotional coaching.

The future firm cannot be only a book of business.

It has to be an organism.

That is one of Shawn’s quiet insights. The firm is not only serving clients today. It is also being built for the next generation of advisors. Shawn has lived through a succession process with Tom. Now, in his early forties, he is already thinking about how to create the path for the next generation inside Note.

That long-term orientation is not accidental. It is one of the privileges of independence. A privately owned firm can make decisions for the next five, ten, or fifteen years, not just the next production cycle.

That kind of patience is becoming rare. And valuable.

Fee Compression Was the Wrong Fear

For years, the advisory industry talked about fee compression. Robo-advisors were coming. Passive investing was expanding. Technology would commoditize portfolio management. The fear was that advisors would not be able to charge what they once charged.

Shawn sees the issue differently. The real question is not only fee compression. It is value expansion.

What else does the advisor do for the client beyond delivering market exposure?

That question is the future of the business.

If an advisor is charging a fee only to build an asset-allocated portfolio, the pressure is real. Technology can already do much of that cheaper, faster, and often well enough. AI will accelerate that pressure. Clients will become more informed. Younger heirs will ask sharper questions. Public tools will make previously elite information available to almost anyone willing to ask the right prompt.

But if the advisor is helping a client navigate cash flow, taxes, insurance, estate planning, retirement transitions, business sales, family conversations, emotional decision-making, and relationship with money, the value proposition changes.

The advisor is no longer just managing money. The advisor is helping organize a life. That is harder to commoditize.

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The Six Pillars and the Circle Around Them

Note Advisors organizes its planning work around six core pillars: cash flow, insurance, taxes and tax planning, investments, retirement planning, and estate planning. Those pillars are technical. They matter. They are the table stakes of serious financial planning.

But Shawn adds something else around them.

A circle.

That circle is the client’s relationship with money.

That is where the conversation becomes especially important. Technical advice can be correct and still fail. A plan can be mathematically sound and emotionally unusable. Two spouses can receive the exact same recommendation and hear two completely different things. One may feel relief. The other may feel fear. One may see opportunity. The other may see loss of control. One may be ready to retire. The other may quietly wonder what retirement will do to their identity.

This is where most financial plans break down. Not in the software.

In the human.

Shawn tells a familiar story. A client comes in at 60 and says they want to retire at 65. The advisor does the work, runs the numbers, and discovers the client can retire at 62. The client stays on track, reaches 62, and the advisor says, “You can retire.”

Then the client pauses and says, “Yes, but what would I do?”

The math was right. The plan was incomplete. That moment is the difference between financial planning and life planning.

The Wealth Coach

To solve for that gap, Note Advisors brought a wealth coach, Christine, onto the team. Shawn acknowledges that he does not know how many firms have done something similar, but the logic is clear. Christine helps bridge the technical and emotional sides of money.

She is not there because the firm lacks technical skill. Shawn is clear about that. Note Advisors still must be excellent at the core advisory work. The investment advice has to be sound and is table stakes. The planning has to be right. The tax thinking has to be thoughtful. The estate conversations have to be integrated. The bed still has to be comfortable. The lights still have to turn on.

But wealth coaching adds another dimension.

It helps the team understand why a client may not act on good advice. It helps translate between the numbers and the meaning a person makes from those numbers. It helps advisors become better communicators. It helps couples, families, and individuals see their relationship with money more clearly.

That is not soft. That is strategic. Because advice that is not acted upon is not fully delivered.

The Client Who Just Wants to Play with Her Grandkids

One of the most powerful examples Shawn shares is about a successful executive who had managed her own finances for years. She met with him, went away, and then years later called back.

She was ready.

The reason was not that she suddenly became less capable. It was not that she did not understand money. It was not that she could not manage a portfolio. It was that she had retired and found herself on the floor playing with her grandkids while thinking about the stock market, distributions, Medicare premiums, and whether she was taking too much money.

She did not want her mind split between the life she had earned and the portfolio she was still managing. She wanted to play with her grandkids. That is why people hire advisors.

Not always because they cannot do the work. Sometimes because they no longer want the work taking up the most sacred parts of their attention.

For Shawn, those are the right clients. Intelligent, capable people who understand there is value in delegating to a professional so they can spend their time on something more important.

That is a profound reframe. The advisor is not only managing assets. The advisor is returning attention.

AI, Table Stakes, and the Return of Humanity

The conversation eventually moves into AI, because every serious conversation about financial advice now has to. Shawn is not dismissive of it. He uses it. His team uses it. He believes AI can make people on the technical side more productive and give front-facing advisors more time with clients.

But he does not think AI replaces the core human work of advice.

In fact, he believes the opposite may happen. As AI commoditizes the technical layers, the human layers become more valuable. The advisor who only manages a portfolio may be exposed. The advisor who uses AI to increase proactive service, deepen conversations, improve responsiveness, and solve more integrated wealth problems may become more valuable.

Chris frames it through a hotel metaphor. Every hotel room needs a bed, lights, a shower, and basic functionality. Those are table stakes. In financial advice, portfolios, tax awareness, planning tools, and investment access are becoming table stakes too. In the near future, saying “we use AI” may be like saying “we have electricity.” It will not be a differentiator. It will be expected.

So what will clients pay for?

The experience.

The trust.

The humanity.

The relationship.

The feeling that when they walk into the advisory equivalent of the Ritz, someone sees them, understands them, hands them the room key with care, and knows why they are there.

Technology should not turn advice into a phone tree. It should free advisors to be more human. That may be the central thesis of the episode.

The Empowered Client

One of the most important disruptions AI will bring is not simply advisor productivity. It will empower clients.

Clients will walk into meetings with AI-generated questions. They will run tax strategies through ChatGPT, Gemini, Claude, or whatever tool they prefer. They will ask about estate structures, asset protection, deductions, Roth conversions, insurance strategies, concentrated stock, business succession, and investment ideas with more context than prior generations ever had access to.

That does not mean they will always be right. In fact, that is why advisors still matter.

A client may ask AI whether they can do something and get a technically plausible answer, but miss the follow-up question that changes everything. Yes, you might be able to do that. No, you may not get the deduction you think you are getting. Yes, that strategy works in one context. No, it does not fit your entity structure, family dynamics, risk tolerance, or tax profile.

The client will be more informed, but not necessarily wiser. The advisor’s job will shift from gatekeeper of information to interpreter of context. That is a better job.

And a harder one.

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The Great Wealth Transfer Is Also a Great Trust Transfer

Shawn sees another major shift underway. The older generation, especially those in their mid-70s and beyond, often held money close to the vest. They did not talk openly about wealth. Children would find out when the parents died.

But Shawn sees many baby boomer clients behaving differently. They are more willing to talk with their children about money. They are asking Note Advisors to help the next generation. They want their children, often in their late twenties and thirties, to start earlier than they did. They understand that if they had begun with better planning when they were newly married, buying their first home, having children, and building careers, the compounding effect could have been enormous.

That creates a major opportunity and responsibility. The great wealth transfer is not just about assets moving from one generation to another. It is about trust moving, or failing to move, from one advisory relationship to another.

Most inherited assets do not automatically stay with the parents’ advisor. The next generation will decide whether the advisor understands them, communicates with them, respects their preferences, uses technology well, and can help them navigate a different world than the one their parents lived in.

This is why multigenerational teams matter. This is why emotional intelligence matters. This is why the firm cannot be built only around one founder’s relationships.

If the advisory firm does not evolve, the assets may move. Not because the old advisor was bad. Because the new client was never truly served.

Succession as Stewardship

Shawn is also thinking about succession inside his own firm. He is in his early forties, but he has already seen how long succession takes when done well. He watched and lived through the process with Tom. He understands that waiting until your late fifties or sixties to start thinking about succession may be too late.

He wants to create a path for the next generation of Note Advisors.

That includes ownership. It includes infrastructure. It includes training. It includes culture. It includes giving younger advisors a firm worth inheriting and a reason to stay. He has attended succession conferences and is interested in internal succession, employee ownership, and building a legacy firm rather than simply selling into a roll-up machine.

That is a meaningful distinction. There are firms built to be sold. There are firms built to endure. Shawn sounds far more interested in the second.

He wants the next generation of advisors to have a home, but not a cage. A platform, but not a prison. Structure, but not stagnation. Compliance, technology, marketing, and operational support, but also the freedom to serve clients deeply.

That may become a major recruiting advantage. Many advisors love client relationships and business development but do not want to carry the full weight of compliance, HR, cybersecurity, operations, and tech stack management. Others want total independence. The future may require different homes for different kinds of advisors.

Knowing what you actually want becomes more important than copying someone else’s model.

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Buffalo, Roots, and the Long Game

There is something fitting about this story being rooted in Buffalo. Shawn serves clients nationally, but the firm carries a Western New York sensibility: grounded, relationship-driven, practical, salt-of-the-earth, not overly impressed with financial theater.

That matters.

In an industry often seduced by scale, roll-ups, branding, and abstraction, Shawn’s worldview feels anchored. He talks about brick by brick. Day by day. Week by week. Year by year. He talks about loving the work. He talks about showing up. He talks about the marathon mindset.

That is how durable advisory firms are built. Not all at once. Not through one clever campaign. Not through one acquisition.

Through years of doing the work, serving the people in front of you, learning where the model is broken, and having the courage to rebuild before the market forces you to.

The Human Premium

The deeper message of this episode is that the future of advice will not be less human because of technology.

It will be more human because of AI technology, if advisors choose correctly.

AI can produce answers. It can summarize. It can model. It can draft. It can compare. It can automate. It can analyze. It can reveal what used to be hidden behind expensive research, proprietary software, or specialized education.

But it cannot fully know what retirement means to a person whose identity is tied to work. It cannot feel the silence between spouses when one agrees out loud but disagrees internally.

It cannot understand the fear in a client who has enough money but does not feel safe. It cannot replace the trust that comes from years of being steady when life is not.

It cannot build a legacy firm unless humans decide what kind of legacy they are building. That is where Shawn’s work lives.

In the space between the technically correct answer and the human being who has to live with it.

Closing Thought

This ATOMIQ LEVEL conversation with Shawn Glogowski is a reminder that the financial advisory profession is not dying. It is being sorted. The advisors who only sell products may struggle. The advisors who only manage portfolios may be compressed.

The advisors who hide behind institutions may find the cage safer but smaller. The advisors who ignore AI may fall behind.

But the advisors who combine fiduciary independence, technical competence, emotional intelligence, team-based service, multigenerational continuity, and a willingness to use technology to become more human may be entering the most important era of their careers.

For clients, this episode is a reminder that the right advisor should help you do more than grow a portfolio. They should help you live the life the portfolio is supposed to support.

For advisors, it is a reminder that the future belongs to those willing to expand value before the market compresses fees. For families, it is a reminder that money decisions are rarely just money decisions. And for anyone trying to understand what comes next in wealth management, Shawn’s story offers a grounded, practical, human answer.

The future advisor will not merely manage assets. The future advisor will help people make meaning, take action, build trust, transfer wisdom, and protect the one asset no market can replace.

Time.

Press play on this episode with Shawn Glogowski of Note Advisors, and you will hear why the next era of fiduciary wealth may be less about replacing humans with machines and more about using machines to give the best humans more room to serve.

Because wealth advice was never supposed to end with the answer. It was supposed to help someone become ready for the next chapter.

The real risk is doing nothing!

~Chris J Snook

Connect with Sam Strasser

Before you read the feature below or listen to the episode, connect with Sam Strasser, CEO and co-founder of Treasure Financial.

Linkedin: Sam Strasser

Company: Treasure Financial

Sam is building at the intersection of corporate treasury, fintech infrastructure, registered investment advisory services, stablecoin reserves, agentic AI, and small business cash optimization. His work is aimed at a problem almost every business owner understands but too few solve well:

What should your company be doing with idle cash?

Treasure Financial exists to help businesses put every dollar to its highest and best use, without forcing owners, operators, CFOs, founders, and fintech platforms to manually become corporate treasury experts overnight.

TL;DR Key Takeaways

Sam Strasser grew up in an entrepreneurial family, surrounded by people who built companies, sold companies, and treated business creation as a natural way to move through the world.

Treasure Financial is Sam’s fourth company. The idea came from a pain point he experienced directly in a previous business, where the company had about ten months of cash sitting on the balance sheet, and the bank was unwilling to offer a better yield.

A conversation with the CFO of Airbnb opened Sam’s eyes to the power of corporate treasury. At Airbnb, treasury was not a back-office afterthought. It was a meaningful financial engine that helped the company put cash to better use.

Sam applied similar treasury tactics to his own company and says it increased the bottom line by about 7% that year. That became the aha moment behind Treasure Financial.

Treasure’s mission is to democratize corporate treasury for small and medium-sized businesses, giving them access to cash optimization strategies usually reserved for larger companies.

The platform helps companies identify idle cash and allocate it across managed money market, managed treasury, and managed income strategies, with a focus on after-tax yield, liquidity, safety, and avoiding unnecessary concentration in one institution.

Treasure is both a software-first technology company and a registered investment advisor. Sam sees the RIA structure as what enables the firm to serve customers properly while building the technology layer around treasury management.

Treasure serves direct business customers and also offers an API product for fintechs, neobanks, FX platforms, stablecoin companies, and other financial technology businesses that want to embed treasury offerings without building the regulatory and investment infrastructure themselves.

The company has around 350-plus platform customers and roughly 10 API clients, with the API side becoming a larger focus as fintech platforms look for regulated, professional treasury infrastructure.

Treasure uses Apex as a custodial partner and charges a management fee that starts around 35 basis points, with lower tiers based on deposit size.

The typical minimum can be as low as $10,000, but Sam says the average entry point is around $250,000, and the average customer holds around $5 million with Treasure. The company presently serves small businesses as much as $125 million in revenue.

A major theme of the conversation is that most companies still leave cash sitting in checking accounts, earning very little, while banks use those deposits to generate revenue. Treasure is built to shift more of that value back to the business owner.

Sam has deployed more than 75 internal agents at Treasure with a team of only seven full-time humans. Agentic AI has changed how the company works, hires, serves customers, manages operations, and thinks about scale.

Sam believes advisers will still matter in an AI world, but their role will shift. They will need to become more like system designers, technologists, fiduciary interpreters, and relationship-centered guides.

The deeper message: corporate treasury is no longer just for giant companies. In an era of AI, stablecoins, cash preservation, changing rate environments, and compressed business margins, every serious owner-operator needs to ask whether their idle cash is working as hard as they are.

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Why You Should Listen to the Full Episode

This ATOMIQ LEVEL conversation with Sam Strasser is not just a fintech interview or an RIA of the future. It is a story about a founder who saw a hidden inefficiency sitting on his own company’s balance sheet, followed that frustration into the world of corporate treasury, and built Treasure Financial to bring institutional-grade cash optimization downstream to the small and medium-sized businesses that banks too often overlook.

It is about why the cash sitting in your business account may be one of the most underutilized assets in your entire enterprise.

It is about why large companies have long understood that treasury is a strategic function, while smaller businesses have been trained to treat idle cash as something that simply sits at the bank.

It is about why the bank’s incentive is not always your incentive.

It is about what happens when cash preservation, after-tax yield, liquidity management, stablecoin reserves, API infrastructure, and agentic AI all collide inside one increasingly important category.

It is also about the future of advisory work. Sam believes AI will change the role of advisers, not eliminate the need for fiduciary responsibility. The adviser of the next era may need to understand technology, systems, workflows, agents, compliance, investment architecture, and human relationship management all at once.

Most of all, this episode is about stewardship:

Stewardship of cash.

Stewardship of business.

Stewardship of time.

Stewardship of family.

Stewardship of the future humans who will inherit whatever systems we build now.

Press play on this conversation with Sam Strasser of Treasure Financial if you are a business owner, founder, CFO, adviser, fintech builder, stablecoin operator, or family office trying to understand why corporate treasury is becoming a front-line wealth strategy.

Because in a world where every dollar matters, idle cash is no longer neutral. It is a decision.

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An Owner Operator Who Found Treasure in Idle Cash

Before Sam Strasser became the CEO and co-founder of Treasure Financial, before he was building corporate treasury infrastructure for small and medium-sized businesses, before he was talking about stablecoin reserves, agentic AI, embedded treasury APIs, liquidity ladders, after-tax yield, and the future of fiduciary technology, he was a founder with too much cash sitting in the wrong place.

That is where the story begins.

Not with a market thesis. Not with a pitch deck. Not with a consultant’s white paper about fintech disruption. But with a problem on a balance sheet.

Sam had built companies before. Treasure was not his first venture. It was his fourth. He had grown up in a family of entrepreneurs, with a father who had started and sold several companies and a broader family culture where building a business was not some exotic life path. It was normal. It was what people did when they saw a problem and believed they could bring something better into the market.

That background matters because Sam did not come to treasury strategy as an outsider fascinated by financial jargon. He came to it as an operator.

He had cash in a company. The cash was sitting there. And the bank was not helping.

The Bank Said No

At his previous company, Sam had roughly ten months of cash on the balance sheet. Like any responsible operator, he looked at that cash and wondered if it could be doing more. He went to the bank and tried to negotiate a better yield.

The answer was not useful.

The bank was not willing to change the economics in a way that meaningfully helped the business. That moment revealed something every business owner eventually learns, but not always clearly enough: the bank’s incentive and the business owner’s incentive are not identical.

The business owner wants safety, liquidity, access, yield, flexibility, tax efficiency, and operational simplicity.

The bank wants low-cost deposits that stay put.

That mismatch is easy to ignore when rates are near zero or cash balances are small. But when a company has meaningful reserves, when the rate environment changes, when margins matter, and when every dollar needs to contribute to the enterprise, idle cash becomes more than a line item.

It becomes a question of stewardship. Sam went looking for a better answer. That search led him to the world of corporate treasury.

The Airbnb Aha Moment

The breakthrough came when Sam connected with the CFO of Airbnb. That conversation opened his eyes to how large companies think about cash. At companies like Airbnb, treasury is not merely an administrative function. It is not just “where the cash sits.” It is a sophisticated internal discipline designed to manage liquidity, risk, yield, duration, tax implications, banking relationships, capital efficiency, and the highest and best use of every dollar.

Sam was struck by the scale of the impact. He says that at Airbnb, a meaningful portion of revenue was coming from treasury activity. Whether someone hears that as a precise number or simply as an illustration of magnitude, the lesson was clear: corporate treasury could materially affect the economics of a business.

So he began applying some of those tactics to his own company. The result, he says, was a roughly 7% improvement to the bottom line that year. That is not a rounding error.

For a founder, that kind of improvement does something to the imagination. It turns a frustration into a thesis. It turns a bank account into a market. It turns a hidden operational discipline into a product opportunity.

Sam realized that the problem he had experienced was not unique. Thousands of small and medium-sized businesses were likely sitting on idle cash without the tools, guidance, infrastructure, regulatory wrapper, or time to manage it well.

Large companies had treasury departments. Smaller companies had checking accounts. Treasure Financial was born in that gap.

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Democratizing Corporate Treasury

In 2018, Sam sold his shares in his previous company to his partner and went full-time into building Treasure. The mission was simple to say and hard to execute: democratize corporate treasury for small and medium-sized businesses.

That phrase can sound polished, but the underlying idea is practical. Treasure was designed to help companies identify idle cash and allocate it into strategies that could generate better returns while preserving liquidity and managing risk. The platform takes a process that would otherwise require specialized expertise and turns it into something a business can implement quickly.

Sam describes the onboarding as taking around ten minutes. Once a business is signed up, Treasure helps identify idle cash and allocate it across three core investment vehicles: managed money market, managed treasury, and managed income. The portfolios are built with an after-tax yield perspective, with attention to liquidity, safety, concentration risk, and the macroeconomic environment.

That after-tax point matters. Many business owners compare headline rates without fully understanding entity structure, tax treatment, treasury bills, money markets, C-Corps, pass-through entities, state taxation, and the different implications of where cash sits. Treasure’s job is not just to chase yield. It is to help make sure the cash is being put to its highest and best use in a way that fits the company’s actual needs.

This is the difference between a teaser rate and a treasury strategy.

The Fourth Company and the Almost-Failed Round

Treasure may have begun with a strong insight, but the path was not smooth. Sam initially tried to bootstrap the company. That was his instinct. He had built before, and bootstrapping had appeal. But after roughly six months, it became clear that if Treasure was going to get off the ground and scale properly, it would need outside capital.

The first funding round began around late 2019. The company had a strong lead investor and was looking to raise roughly $2 million to $2.5 million.

Then COVID hit. The round fell apart.

The financial institution that had been prepared to lead had to reduce its ownership percentage because of a regulatory change. It could no longer play the same role. At the same time, fear and uncertainty locked up capital across the market. Investors pulled back. The world froze. For a minute, Sam did not know if Treasure would even get started, let alone make it to the next stage.

But the company kept plugging away.

Eventually, Catalyst came in as the first major investor, putting in roughly $1 million to $1.5 million. The team hit the ground running, scaled from there, and later brought on additional investors, including Peter Thiel and Jump Capital.

That part of the story matters because fintech infrastructure businesses can sound inevitable once they exist. In hindsight, people can look at Treasure Financial and say, of course, small businesses need better treasury management. Of course, cash optimization should be automated. Of course, fintechs and stablecoin companies need embedded treasury APIs.

But in real time, companies are built through fragile windows.

A round almost dies. A regulatory change alters the cap table. A pandemic locks up capital. A founder decides whether to keep going. That is the part of company building that the press release never captures.

Software First, RIA by Necessity

One of the most interesting tensions in Treasure’s identity is that it is both a software company and a registered investment advisor. Sam is clear that Treasure thinks of itself as a software technology company first. The company is constantly working on code, algorithms, automation, operations, and increasingly agentic AI.

But the ability to serve customers in the way Treasure does requires the RIA structure. That combination matters. The firm is not simply a fintech dashboard. It is not simply a bank account alternative. It is not simply a yield product. It is a technology layer wrapped around a regulated advisory function designed to help businesses manage short-duration cash and treasury needs.

That regulatory side creates responsibility. It also creates a moat.

In a world where someone can claim to rebuild almost any SaaS feature in a weekend, regulated financial infrastructure remains different. The software matters, but so does custody. Compliance matters. Investment advisory status matters. Operational controls matter. Liquidity management matters. Customer trust matters.

You can copy a screen. You cannot instantly copy eight years of regulated operating context.

The Customer: From Owner-Operators to Stablecoin Companies

Treasure’s customer base has expanded across several distinct segments. On the direct platform side, the company serves businesses that want to manage corporate cash more effectively. Sam says the minimum can be as low as $10,000, but the average entry point is closer to $250,000, where the strategy begins generating more meaningful returns. The average customer holds around $5 million with Treasure, and the company works with businesses up to roughly $125 million in revenue.

These customers can include owner-operated businesses, venture-backed companies, and other corporate clients with different liquidity needs. A venture-backed startup that just raised a round may be able to ladder cash more predictably. A manufacturing business may have more irregular liquidity demands. A stablecoin company may need extreme liquidity because tens or hundreds of millions of dollars can move in and out on a daily or near-daily basis.

The point is flexibility.

Treasure connects to a company’s accounting data so it can better understand when cash may be needed and where that cash should sit. The goal is to make sure the company always has access to its funds while the money earns as much as it reasonably can during the time it is sitting there.

That is the core promise. Liquidity first. Yield intelligently. No unnecessary lockup.

The API Layer

Treasure is also building through an API product that serves fintech platforms, neobanks, FX companies, stablecoin businesses, and other financial startups that want to offer treasury functionality without building the entire regulated infrastructure themselves.

This is where the business becomes especially interesting. Treasure can allow another platform to roll out a treasury offering to its user base in as little as 30 days, taking on much of the compliance and investment infrastructure burden because Treasure is the RIA.

Sam describes working with fintechs and stablecoin companies where Treasure acts as the reserve partner, managing investments for dollars converted into stablecoins such as USDC. The company also actively manages short-duration portfolios and adjusts treasury strategies as the yield curve changes.

When the yield curve moves from inverted to normalized, your treasury strategy has to change. That is not something most founders, CFOs, or fintech platforms want to manage manually every week.

Treasure does that work.

On the direct platform side, Treasure has hundreds of customers. On the API side, Sam says the company has around 10 API clients and has been increasing its focus there over the past year. That makes sense. As financial platforms proliferate and everyone looks to embed more value into their product, treasury-as-infrastructure becomes a category with obvious demand.

Not every fintech wants to become an RIA. Not every neobank wants to build treasury expertise. Not every stablecoin company wants to manage short-duration reserves alone. Treasure Financial can sit underneath them.

The Bank’s Float Is the Business Owner’s Opportunity Cost

One of the most important parts of the conversation is Sam’s explanation of the banking system incentive. Most companies still leave funds sitting in checking accounts, earning very little. Meanwhile, banks use those deposits to make loans, manage their balance sheet, and generate revenue.

That is not evil. It is banking. But the business owner should understand the trade.

If a company has $5 million or $10 million sitting in an account earning 25 basis points or 50 basis points while other short-duration options may offer materially more, the opportunity cost can be meaningful. As rates decline, the gap between what banks pay on deposits and what active treasury management may be able to capture becomes even more important.

Sam’s point is that business cash should not automatically become someone else’s cheapest funding source.

The cash belongs to the business. The benefit should accrue to the business. Treasure exists to help more of that value flow back to the company that earned the money in the first place.

That message should land with any owner-operator who has spent years fighting for revenue, margin, payroll, customer retention, and survival. If you worked that hard to earn the cash, why would you let it sit unexamined?

The Difference Between a Cash Account and a Treasury Strategy

The conversation also touches on platforms like Bill.com offering cash accounts and yield-like products. Sam’s distinction is important. Many platforms can offer attractive rates as an acquisition tool. Sometimes those rates are capped, subsidized, tiered, or structured as marketing.

That does not make them useless. But it does make them different from a treasury strategy.

Treasure is not trying to win customers with a teaser rate. The firm’s management fee starts at around 35 basis points and can decline based on the amount deposited. The yield a customer sees is meant to reflect the actual treasury strategy rather than a promotional acquisition offer.

That difference matters to serious operators. If you are managing $250,000, $5 million, or $25 million in corporate cash, you are not simply looking for a cute rate on the first slice of cash. You are looking for a repeatable system that helps manage liquidity, risk, duration, tax implications, access, and yield over time.

A cash account is a feature. Treasury is a discipline.

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Agentic AI Inside the Treasury Company

Then the conversation takes a turn. Sam reveals that Treasure has deployed more than 75 agents inside the business while operating with only seven full-time humans.

That moment reframes everything.

Treasure is not merely building a treasury platform for the AI era. It is becoming an AI-native operating company itself. Starting in late 2024 and through 2025, Sam spent significant time resetting the company’s operational strategy around agentic AI. The agents now help across compliance, engineering, customer service, and internal operations.

That changes how the company hires. It changes how roles are defined. A customer service role becomes less about manually responding to every message and more about managing a fleet of agents, adjusting prompts, monitoring data, improving workflows, and knowing when a human needs to intervene.

The job shifts from doing the task to designing and supervising the system that does the task.

That is a profound change.

Sam is careful, though. He is not recklessly throwing agents into every customer-facing interaction. Treasure is being more patient where live product and customer interaction are concerned. Internal operations are one thing. Regulated customer-facing financial workflows are another. There is a wall that should not be crossed casually.

That is the right lesson for the age of agents. Move fast where the blast radius is contained. Move carefully where trust, money, compliance, and customer harm are at stake.

AI, Family, and the Return of Time

One of the most human moments in the episode comes when the conversation moves from agents and operations to fatherhood. Sam has three young kids. Chris does too. The question becomes bigger than productivity.

What is all of this for?

Sam’s answer is practical and moving. The agents free up time. They make work-life balance more achievable. They allow him to spend more focused time with his kids and family without feeling irresponsible about the business. Instead of feeling like every email or text requires immediate personal response, he can trust systems to raise the flag when something truly needs his attention.

That is a different frame for AI. Not just replacing labor.Not just scaling output. Not just reducing cost. Restoring attention.

The founder who once had to carry every operational burden can now spend more time on the creative side, the strategic side, the family side, and the human side. Sam sees agents as shifting humans back toward ideation, creation, architecture, and direction. The agents execute more of the work. Humans become the dreamers, designers, supervisors, and stewards.

That may be one of the most important takeaways from the entire conversation. The best use of AI may not be making humans irrelevant. It may be giving humans back the space to be more human.

The Adviser as Technologist

The episode also explores what AI means for financial advisers. Sam does not believe advisers disappear. He believes the role changes.

If a person hands everything over to an agent but does not understand macroeconomics, investment strategy, fiduciary responsibility, risk, or how to evaluate what the agent is doing, they may be trusting a system they cannot properly supervise. That creates a continued need for investment advisers, but the adviser of the future may look different.

Sam suggests advisers will become more like technologists.

Chris refines that idea: not necessarily coders, but designers of systems. Advisers need to understand how agentic AI, workflows, operating architecture, and customer experience can improve their business. They need to know how technology can reduce operating costs, expand service, personalize client experience, and help them deliver more value at each moment of truth.

The investment management function itself may become increasingly automated and commoditized. But the fiduciary function does not vanish. The relationship function does not vanish. The ability to interpret, contextualize, design, and guide becomes more important.

The adviser of the future will not be paid merely to pick investments. They will be paid to architect trust.

Stablecoins and the New Movement of Money

Sam is also excited about stablecoins and the way they are changing how money moves. Treasure already works with stablecoin companies as a reserve partner, but the opportunity goes beyond reserve management.

Stablecoins compress settlement time. They make cross-border flows more programmable. They create new windows where money can be invested, moved, allocated, and optimized across time periods that were previously too short or operationally impractical to matter.

Sam gives the example of investing on rails during a one-to-five-hour flow window while funds are being sent from the United States to Mexico. Five years ago, that kind of idea would have sounded borderline impossible. Now it is becoming productizable.

That is where treasury becomes more than yield on idle cash. It becomes programmable liquidity infrastructure.

As stablecoins mature, as digital dollar rails become more common, and as fintech platforms embed more financial functionality, the ability to manage cash intelligently across very short windows may become a major source of value. Money is learning to move faster. Your treasury has to learn to think faster, too.

Cash Preservation in an Uncertain World

The macro backdrop matters. Sam notes that uncertainty creates tailwinds for Treasure because cash preservation becomes top of mind. When business owners get nervous, many instinctively move funds back into checking accounts or plain cash equivalents. But that can leave a lot of money on the table.

The rate environment is changing. Money market yields may decline. Checking account yields may drop back toward very low levels. The Federal Reserve may cut. The yield curve may normalize further. In that world, the difference between passive cash and managed treasury can become more visible.

But the point is not simply chasing the highest number on a screen.

The point is building a cash strategy that matches liquidity needs, duration tolerance, tax structure, entity type, and operating reality.

A business with irregular working capital needs cannot manage cash the same way as a venture-backed startup with a fresh round in the bank. A stablecoin issuer cannot manage cash the same way as a family-owned services company. A C-Corp may think differently than a pass-through LLC.

Treasury strategy has to fit the business. That is what Treasure is trying to automate and professionalize.

The Hidden Wealth Strategy for Owner-Operators

For the Wealth Matters audience, this conversation should feel especially relevant because so much first-generation wealth is created inside operating businesses. Many high-net-worth individuals are not rich because they inherited a public stock portfolio. They built a company. They own a practice. They operate a closely held business. They run an advisory firm, service company, real estate enterprise, family business, professional practice, or growing startup.

For those people, the business balance sheet is not separate from the wealth plan. It is the wealth plan.

That is why corporate treasury deserves more attention. Idle business cash affects returns, resilience, tax planning, liquidity, acquisition readiness, lender confidence, owner distributions, and downside protection. In uncertain markets, how a company manages cash can shape whether it survives, grows, acquires, waits, or gets forced into bad decisions.

Sam’s work brings a family-office discipline into the operating company layer. That is the larger opportunity.

Not just better yield.

Better stewardship.

The Founder Building for the Next Operating Model

Sam’s story is compelling because he is not just talking about the future. He is living inside it.

He is running a regulated financial technology company with seven people and more than 75 internal agents. He is serving direct business customers and API customers. He is managing treasury strategies across changing yield curves. He is supporting stablecoin infrastructure. He is thinking about advisers as future system designers. He is building in Scottsdale after time in Santa Monica and San Francisco. He is a father thinking about what technology gives back to family life. He is a founder who found his market by solving his own problem.

That combination is rare. It makes Treasure more than a yield platform story.

It makes it a case study in what the next generation of fintech operating companies may look like. Lean teams. Agentic workflows. Regulated infrastructure. Embedded APIs. Stablecoin relevance. Human judgment at the center. Customer cash, treated as a strategic asset, and put to work.

Closing Thought

This ATOMIQ LEVEL conversation with Sam Strasser is a reminder that some of the most important innovations in wealth are not always flashy. They do not always begin with a new asset class, a giant market call, or a speculative moonshot.

Sometimes they begin with a founder staring at idle cash and asking a better question.

Why is my company’s money working harder for the bank than it is for me?

That question led Sam into corporate treasury. It led him to Treasure Financial. It led him into a category that may become increasingly important as business owners, advisers, fintechs, stablecoin companies, and family offices realize that cash management is no longer a passive administrative function.

It is a strategy. For business owners, this episode is a reminder to look at the cash already sitting inside the company.

For advisers, it is a reminder that technology will not remove fiduciary responsibility, but it will reshape how value is delivered.

For fintech builders, it is a reminder that regulated infrastructure can become a powerful platform layer. For parents and founders, it is a reminder that AI may give us more than speed. It may give us back time.

Press play on this episode with Sam Strasser of Treasure Financial, and you will hear why corporate treasury, stablecoins, agentic AI, and small business cash management are converging into one of the most practical wealth conversations of the decade.

Because your cash is already doing something. The only question is whether it is working for you.

The real risk is doing nothing!

~Chris J Snook

Before you read the show notes below or listen to the episode, connect with David Lambert, Managing Director at Right Side Capital Management, and learn more about the firm’s “VC with no BS” approach to early-stage investing.

Right Side Capital LinkedIn: https://www.linkedin.com/company/right-side-capital-management/

David Lambert LinkedIn: https://www.linkedin.com/in/davidlambert55/

Right Side Capital X: https://x.com/RightSideCapVC

David and the Right Side Capital team have built one of the more distinctive venture models in the market: ultra-diversified, quantitative, data-driven, pre-VC stage investing focused on capital-efficient technology startups raising smaller early rounds most traditional venture firms ignore.

This conversation is for founders, angel investors, family offices, wealth managers, venture skeptics, allocators, and anyone trying to understand how early-stage investing changes when AI collapses the cost of building, launching, and scaling software companies.

TL;DR Key Takeaways

David Lambert grew up in Denver and moved to the San Francisco Bay Area in the late 1980s to attend Stanford. Long before “entrepreneur” was a polished career identity, he was already wired that way, from mowing lawns to selling cake door-to-door as a kid.

He had only one truly “normal” job: working as a Wells Fargo bank teller during freshman year of college. After that, his path was almost entirely entrepreneurial.

David built and ran a computer hardware company for more than a decade, serving Bay Area corporate clients and dot-com-era companies. He nearly got wiped out when the dot-com bubble burst, then turned the business back to profitability.

He later launched a software company, Work Metro, focused on online job boards, raised capital from angels and venture investors, and sold it to a competitor in early 2008.

Right Side Capital became David’s third startup. Though technically a venture capital firm, he describes it more like an operating company whose business happens to be funding startups.

The firm’s model was born from a Black Swan insight: most successful technology startups are positive black swans. They look unlikely or unnecessary in foresight, then obvious in hindsight.

Instead of trying to pick the next Google, Facebook, or generational founder, Right Side Capital built a quantitative model designed to capture exposure to many potential positive black swans through extreme diversification.

The firm invests at the “pre-VC” stage, often in small rounds traditional professional investors overlook. Each fund may include hundreds of investments, compared with the 15 to 30 companies typical of many venture funds.

Right Side does not evaluate each startup by asking, “Will this specific company win?” It evaluates companies as profiles inside a larger pool, more like an insurance actuary or credit underwriter evaluating expected outcomes across many similar risks.

David believes price matters enormously. By investing early, in capital-efficient companies, at reasonable valuations, Right Side can make $80 million to $200 million exits meaningful in a way that many traditional VC firms cannot.

The AI era may be a major tailwind for Right Side’s model because the cost and time required to build software, launch products, automate operations, and reach early revenue is collapsing.

The deeper message: venture capital may not be as much about genius picking as the industry mythology suggests. Sometimes the better question is not whether you found the next superstar. It is whether you are sitting at the right table, at the right price, with enough exposure to the right category of opportunity.

Why You Should Listen

This ATOMIQ LEVEL conversation with David Lambert is not just a venture capital interview. It is a story about a lifelong entrepreneur who grew up selling, building, testing, surviving, and learning before turning that pattern recognition into a venture model that challenges almost every sacred belief of traditional early-stage investing.

It is about a kid in Denver who sold cake door-to-door, mowed lawns, came to Stanford before entrepreneurship was cool, refused the corporate path, built a hardware company, survived the dot-com crash, launched a software company, sold it before the financial crisis, then helped build Right Side Capital around the idea that the venture industry may be overconfident in its ability to pick winners.

It is about why successful startups often look like positive black swans: improbable before they work and obvious after they win.

It is about why diversification, price discipline, capital efficiency, and exposure to many early-stage profiles may be a more rational way to capture venture returns than betting the farm on concentrated conviction.

It is about AI, but not in the shallow “AI will change everything” way. David’s framework makes you think about what happens when the cost of building software collapses, when a few hundred thousand dollars can create what used to take millions, when early revenue can arrive faster, when small exits can produce meaningful returns, and when Series A, B, and C rounds may not be as necessary for as many companies as they once were.

Most of all, this is a conversation about seeing the venture game without the mythology.

No BS.

No wizard costume.

No pretending one person can perfectly predict the next outlier.

Just math, markets, founders, price, diversification, and the humility to admit that the future often looks obvious only after someone else has already built it.

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Press play on this conversation with David Lambert of Right Side Capital Management if you want to understand how early-stage venture investing may change in the age of AI, why pre-VC capital could become even more valuable, and why the next wave of company creation may reward investors who know how to capture the category instead of chasing the legend.

Because the future of venture may not belong only to the best picker.

It may belong to the investor who understands how many shots it takes to let the black swans find you.

The Man Who Took the BS Out of Early-Stage VC

Before David Lambert became Managing Director at Right Side Capital Management, before he helped build a venture model designed to fund hundreds of early-stage companies at a time, before he was sitting across from founders and allocators explaining why the traditional VC mythology might be more fragile than people want to admit, he was a kid in Denver learning how to sell.

Not in a classroom.

Not from a pitch deck.

Not from a partner meeting on Sand Hill Road.

From the street, the neighborhood, the front door, and the early realization that if you wanted something to happen, you had to go make it happen.

As a child, David was already entrepreneurial. He had a lawn-mowing business with a friend in high school. Before that, in late elementary school, he remembers baking a cake after school and walking around the neighborhood selling pieces of it to people he did not know. That image says a lot about the man who would eventually build a career around the earliest stage of company formation.

Most people wait for permission. David learned early that customers answer the door.

That instinct followed him west. After high school, he left Denver for the San Francisco Bay Area in the late 1980s to attend Stanford. But this was not the Stanford startup mythology people know today. Entrepreneurship was not yet a glossy career track. There were no polished founder ecosystems, startup bootcamps, pitch competitions, founder influencer accounts, or polished curriculum teaching students how to raise capital and build unicorns.

Even though venture capital existed in the Bay Area, the idea of becoming an entrepreneur straight out of school was still strange. David remembers that when he told people he was starting his own company after graduation, many looked at him as if he were crazy.

Entrepreneurship was not yet a badge. It was a question mark.

Before the Startup World Had a Name

David graduated from Stanford in 1992. He knew plenty of people. He was surrounded by talent. But he knew only one other person who was actually starting a business after school. The idea was still so early that he remembers driving across the Bay Bridge to Berkeley just to buy a book that taught him how to incorporate a company.

That detail matters because it places his story before the playbook.

Today, starting a company can feel almost procedural. Register the entity. Spin up the site. Use Stripe. Create a deck. Launch on Product Hunt. Build a product with AI. Raise a pre-seed round. Post the journey. Join the network. But in the early 1990s, David was not following a trend. He was following a temperament.

He did not want to work for a large company. He had one normal job in his life, as a Wells Fargo bank teller during freshman year. After that, everything bent toward entrepreneurship.

He sold computers. He ran a student painting business. He learned to hire and train crews. He developed the kind of ground-level operating skills schools still rarely teach: how to sell, hire, manage, make payroll, serve customers, recover from mistakes, and keep moving when the theory breaks.

That is one of the first important lessons of this conversation. Entrepreneurship is not learned by admiring entrepreneurs. It is learned by doing the work badly enough times to get better.

The First Company

Right after school, David fell into a small amount of money, roughly $10,000, and used it to start a computer hardware company with a partner, his girlfriend at the time. They launched the month after graduation.

The company built high-end workstations, servers, and networking services for corporate customers in the Bay Area. Over more than a decade, David ran the business through one of the most important periods in Silicon Valley history. He sold to many dot-com 1.0 companies in the late 1990s, then nearly got blown up when the bubble burst, and the music stopped.

That was not an academic business cycle for him. It was an operational reality. Customers disappeared. Demand changed. The market shifted. The companies that looked unstoppable were suddenly gone. David had to turn the business around and get it profitable again.

That kind of experience leaves a mark. It teaches you that growth stories can vanish. It teaches you that funding environments change. It teaches you that the company on the other side of the invoice may not be there tomorrow. It teaches you that market timing matters, but so does survival.

It also teaches you to respect capital efficiency. If you have lived through a bubble bursting, you never quite trust the music again.

The Second Company

While the hardware company was still running, David launched a software company in the early 2000s called Work Metro. The company operated online job boards in different markets, including city-specific sites up and down the East Coast.

This time, the business raised money from angel investors, angel groups, and venture capital firms. David had now experienced both sides of startup building: bootstrapping and venture-backed growth. He had lived the practical realities of sales, operations, capital raising, scaling, market timing, and exit.

Work Metro exited to a competitor in early 2008.

That timing is worth noting. He sold the company just before the financial crisis fully-exposed how fragile the credit and capital markets had become. Again, David found himself near the edge of a macro transition, close enough to understand that the world can change fast and that what seems stable in one moment can become dangerous in the next.

By then, he had built and run companies for years. He had experienced startup creation before it was fashionable, the dot-com boom, the dot-com crash, the rise of online markets, angel investing, venture capital, and exit dynamics.

Then came the third startup. A venture capital firm that did not behave like a normal venture capital firm.

The Third Startup Called Right Side Capital

David describes Right Side Capital as his third startup. Technically, it is a venture capital firm. But in his mind, it is structured more like an operating company whose business happens to be funding startups.

That distinction is important.

Right Side was not born from the traditional VC path. David and his partners did not come out of the standard apprenticeship model of venture capital, where a partner learns the craft, builds a network, writes concentrated checks, takes board seats, reserves follow-on capital, and tells limited partners a story about access, judgment, and pattern recognition.

Instead, Right Side emerged from a different question:

What if early-stage venture returns are less about predicting the one perfect winner and more about building a system that captures enough exposure to positive black swans?

The idea came after David reconnected with someone he had known at Stanford, a friend and future partner named Kevin, who had read Nassim Taleb’s The Black Swan. Kevin became fascinated by the idea that black swan events are things that seem impossible in foresight but obvious in hindsight. He then asked a question that would become foundational to Right Side Capital:

What if black swans bend both ways?

Everyone thinks about negative black swans: crashes, shocks, failures, blowups, and events no one saw coming. But in technology startups, the biggest winners often look like positive black swans. Google looked unnecessary when search seemed solved. Facebook looked redundant when MySpace and Friendster already existed. The best outcomes are often obvious only after they have already happened.

That is the venture paradox. The thing everyone later claims was inevitable was often dismissed before it worked.

Capturing the Black Swan Instead of Predicting It

If the biggest venture returns come from positive black swans, then the rational question becomes whether anyone can reliably identify them in advance. Traditional venture says yes, or at least implies yes. The industry mythology is built around access, taste, judgment, networks, founder selection, pattern recognition, and concentrated conviction.

Right Side asked a different question. What if you stopped pretending you could know the exact company that would win?

What if you invested broadly enough, early enough, and at the right price, so the black swans could emerge inside your portfolio?

That is the core of Right Side’s model. The firm built a quantitative, data-driven approach to what David calls “pre-VC stage investing.” It focuses on a segment of the startup market that most professional investors historically ignored: very small rounds, often a few hundred thousand dollars, raised by capital-efficient technology companies before they enter the standard institutional venture funnel.

The first major difference is diversification. A typical venture fund might hold 15 or 20 companies. A very active fund might hold 30. Right Side funds often hold hundreds, with many funds including 400 or more investments.

The second difference is stage and round size. Right Side plays where many traditional VC firms do not want to operate at scale, in smaller rounds that may be too early, too operationally inefficient, or too unglamorous for conventional funds.

The third difference is perhaps the most important: Right Side does not evaluate a company by primarily asking whether this one specific company will succeed or fail.

It evaluates the company as a profile.

David compares it to the mindset of an actuary building a pool of insurance policies or an underwriter building a pool of loans. The question is not, “Can I perfectly predict this one outcome?” The question is, “If I invested in 50 to 100 companies with this same profile at this same price, how would that pool perform?”

That is a radically different venture mindset. It is less oracle. More underwriting engine.

The Table Matters More Than the Ego

One of the most revealing moments in the conversation comes when David brings up poker. In the 1990s, he was a semi-professional poker player. That experience taught him something that maps beautifully to venture capital.

The most important thing is not always being the best player in the world. It is choosing the right table.

A great poker player sitting with other great poker players may not have a large edge. A solid player sitting with weaker players may have a much better expected return. The same concept applies to investing. The profile matters. The market matters. The price matters. The competition matters. The table matters.

Right Side’s model is built around finding the right table: a segment of early-stage investing where supply and demand are out of balance, where entrepreneurs need small checks, where professional investors are scarce, where valuations can be more attractive, and where diversification can turn idiosyncratic startup risk into a more manageable portfolio-level bet.

That is the quiet brilliance of the model. It does not require pretending every investment is special. It requires knowing which pool is mispriced.

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Why the Venture World Did Not Want to Hear It

David is candid that Right Side’s model was not immediately embraced by the venture world or many professional allocators. In fact, he says they later realized how offensive their model was to the traditional venture worldview.

They violated almost every perceived best practice.

Traditional venture loves concentrated funds. Right Side built ultra-diversified funds. Traditional venture loves follow-on reserves. Right Side generally deploys capital at one stage rather than saving capital to double down later. Traditional venture loves board seats. Right Side does not build the model around taking them. Traditional venture loves the story of the brilliant picker. Right Side built a quantitative engine. Traditional venture loves access and mystique. Right Side published clear criteria and created a fast, transparent funding process.

In the 2010s, that was a hard sell. Quantitative models were still tainted in many minds by the financial crisis. Venture investors and LPs were accustomed to stories about small, concentrated funds generating huge outcomes. The fact that concentrated funds also show up heavily in the bottom quartile did not always get equal attention. The mythology focused on the winners.

Right Side was saying something uncomfortable:

Maybe the industry is confusing variance with skill.

That is not an easy message to sell to people whose careers, reputations, and investment committees were built around the old story.

David tells a powerful story about a fund-of-funds manager who essentially admitted the problem. Right Side checked the boxes, had strong returns, and fit the mandate. But investing in them would have meant admitting that the firm’s existing way of evaluating managers might be wrong.

That is not an investment objection. That is an identity objection. And identity objections are the hardest ones to overcome.

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The No BS Founder Experience

While Right Side’s model challenged LP assumptions, entrepreneurs responded differently. For founders, the value was obvious.

Right Side made its criteria clear. It told founders what it invested in. It asked them to decide whether they were a fit. It created a process. It responded. It could lead and price rounds when angels were circling but hesitant. It could catalyze a small round by providing institutional conviction in a segment where most professional capital did not operate efficiently.

That matters because founders raising $200,000 to $500,000 are often stuck in an awkward part of the market. They may be too early for traditional VC, too small for larger funds, too serious for casual friends-and-family capital, and too capital-efficient to need a giant round. They need enough capital to prove the next thing, but the market often forces them into a time-consuming fundraising maze.

Right Side’s model helped solve that.

It gave capital-efficient founders a professional investor who understood the stage, could move quickly, and did not require the same performative theater of traditional venture.

That is where “no BS” becomes more than branding.

It becomes a process philosophy.

The Collapse in the Cost of Building

One of the most important historical shifts in this conversation is the collapse in the cost of building software.

When Right Side launched, David says it could still cost roughly $500,000 to $1 million to build and launch a software product to the point where you could sell it. That already seemed cheap compared with earlier eras, when the same process might have cost $5 million or $20 million.

But by 2016, 2017, and 2018, that cost had fallen dramatically. In many cases, a founder could build a first version of a software product and test whether customers would pay for it with closer to $100,000.

That changed the market.

More startups could launch. More founders could reach early revenue. More companies could become interesting before raising large amounts of capital. The quality of companies Right Side was seeing, not only improved, but the price often stayed attractive. Where many early investments had been pre-revenue in the early years, later companies were often already launched and generating $5,000 to $20,000 a month in revenue.

That is a powerful setup.

Better quality. Similar price. Less competition. More demand.

That is how markets become attractive. Not because the story is louder, but because the underlying supply-demand imbalance improves.

AI and the Next Collapse

Now David believes another shift is underway. AI is not only changing what startups build. It is changing how much capital they need to build it.

For decades, the cost to create a first version of a software product has been falling. But operational costs did not fall in the same way. Sales, marketing, customer support, engineering, administrative overhead, and scaling still required people, process, and burn. That may now be changing, too.

AI tools are beginning to collapse the cost not just of product development, but of company operation. A small team can build more. A solo founder can move faster. A tiny company can launch, test, sell, support, and iterate in ways that would have required far more capital and headcount just a few years ago.

That matters enormously for Right Side’s model. If a few hundred thousand dollars can now fund a company much further than before, then small early rounds become more powerful. If companies can reach meaningful revenue faster, then early investors may see outcomes sooner. If an $80 million to $200 million exit can happen with less dilution and less capital raised, then those exits can produce real venture returns.

Most traditional VC funds need billion-dollar outcomes because they come in later, pay higher prices, and get diluted across large capital stacks.

Right Side can care about smaller exits because it enters earlier, at lower prices, in capital-efficient companies.

That could become even more important in the AI era. The venture world may be entering a time when the base hit matters again.

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Why Follow-On Capital Is Not the Whole Story

Traditional venture investing often sells a compelling story: invest small early, identify the winners, then double or triple down. It sounds logical. It sounds disciplined. It sounds like learning from the portfolio.

David is skeptical that the math supports the story as cleanly as the marketing suggests.

He also points out a practical issue: if a Series A investor refuses to participate in the Series B, that can send a negative signal to the market. In reality, many funds are forced to continue supporting companies until it becomes socially acceptable not to participate. What looks like strategic follow-on discipline can become reputation management.

Right Side’s approach is different. The firm focuses capital at the stage where it believes the excess return is highest. It does not need to keep chasing later, more efficient, more competitive rounds. That is another way the model violates tradition.

But it is also another way the model stays honest. If the edge is at the pre-VC stage, why leave it?

The Liquidity Reality

David is also clear about the downside. Early-stage venture investing is illiquid. Investors need to understand the time horizon. This is not money someone should expect to access in a year or two. It is better suited for a long-term allocation, particularly for high-net-worth individuals, family offices, and investors who can let capital compound without needing short-term liquidity.

That honesty matters because venture capital can be oversold. The headlines focus on home runs. The reality includes failure, long holding periods, uncertain exits, and the need for patience.

Right Side tries to make the risk more rational through diversification, price discipline, and stage focus, but it does not make the asset class liquid.

Investors still have to live through the cycle.

For the right allocator, that may be acceptable. A small allocation to an ultra-diversified early-stage venture strategy can make sense inside a broader long-term portfolio. But it requires understanding what role the capital is playing.

This is not cash. It is not public equities. It is not short-duration yield farming. It is long-term exposure to early company creation.

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The Future of Venture Without the Costume

The most compelling part of David’s story is that it strips venture capital of some of its costume.

The best venture investors are talented. Networks matter. Judgment matters. Pattern recognition matters. But the industry has often wrapped those truths in mythology. The genius picker. The boardroom savior. The founder whisperer. The concentrated fund that saw the future before everyone else.

Right Side does not reject intelligence. It rejects overconfidence.

Its model begins with humility. You do not know which company will become the positive black swan. You can know which profiles, prices, stages, and market dynamics give you a better pool of exposure. You can know that capital-efficient companies raising small rounds are often ignored. You can know that more shots on goal, taken intelligently, can change the risk curve. You can know that price matters. You can know that the table matters.

That is a more grounded version of venture. Less magic. More math.

Why This Conversation Matters Now

This episode arrives at a moment when the startup world may be entering another structural reset. AI is changing production. Capital efficiency is becoming more powerful. The line between founder, software team, sales team, and operating company is blurring. A company that once needed millions may now need hundreds of thousands. A founder who once needed a full team may now build with agents. A product that once took a year may now ship in weeks or days.

That does not mean every startup will win. In fact, David suggests failure may happen faster too. Companies can be disintermediated sooner. Investors can look wrong in months rather than years. Markets can move faster than diligence processes built for another era.

But that is precisely why a model like Right Side’s becomes interesting. In a world where individual company outcomes may become even more volatile, diversified exposure to the right early-stage profiles may become more valuable, not less.

The black swans may arrive faster.

The question is whether your model is built to catch them.

The Entrepreneur Turned Underwriter of Entrepreneurs

David Lambert’s story comes full circle because he did not become an investor by leaving entrepreneurship behind. He became an investor by turning entrepreneurship into a system.

The kid who sold cake door-to-door became the founder who built hardware through the dot-com boom. The hardware operator became the software founder who sold before the financial crisis. The founder became the investor who understood that early-stage companies are messy, uncertain, and full of randomness. The investor became the architect of a model designed not to eliminate uncertainty, but to price it, pool it, and let enough upside survive.

That is the story of Right Side Capital. Not a venture firm trying to look like every other venture firm. A startup built to fund startups.

A system built by operators who know the difference between a great story and a repeatable edge.

Closing Thought

This ATOMIQ LEVEL conversation with David Lambert is a rare look inside a different venture mindset, one that feels especially relevant as AI rewires the cost of company creation. It is practical, candid, and refreshingly free of the usual mythology.

For founders, it is a reminder that capital efficiency is becoming a superpower.

For investors, it is a reminder that access to early-stage upside does not have to depend entirely on finding the one mythical deal.

For family offices and allocators, it is a reminder that venture exposure can be structured more rationally than the traditional concentrated model often suggests.

And for anyone watching the AI startup explosion, it is a reminder that when the cost of building collapses, the rules of capital formation change with it.

Press play on this episode with David Lambert of Right Side Capital Management, and you will hear why the next era of venture may belong to those who understand the math beneath the madness.

Because in early-stage investing, the future rarely announces itself as obvious. It shows up as a black swan. And only later does everyone pretend they saw it coming.

The real risk is doing nothing!

~Chris J Snook

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Connect with Lori Van Dusen

Connect with Lori Van Dusen, founder and CEO of LVW Advisors, on LinkedIn and through LVWAdvisors.com.

Lori is one of the rare financial leaders who has lived through Wall Street’s old world, helped pioneer the fiduciary advisory movement, built a multibillion-dollar independent advisory firm, and still speaks about wealth in the most human terms possible: empathy, resilience, consensus, family, failure, grace, and the courage to put one foot in front of the other.

You can also read her book, Running with Grace, a Wall Street Journal bestseller that turns personal and professional endurance into a powerful metaphor for leadership, loss, failure, growth, and living with purpose.

TL:DR Key Takeaways

Lori Van Dusen began her career selling copiers before moving to Wall Street in the late 1980s, where she was one of only two women in a class of roughly 300 at the World Trade Center.

Her first day on the trading floor was Black Monday in 1987. With no book of business and nothing to lose, she watched the market crash in real time and asked the person next to her if this happened every day.

Before Wall Street, Xerox sales training taught her one of the most enduring frameworks of her career: SPIN: Situation, Problem, Implication, Need. It became a lifelong model for understanding clients before trying to solve for them.

Lori built her career around listening, asking better questions, and solving the real problem, not the problem as first presented. That lesson was reinforced by her Harvard education and became central to her advisory philosophy.

Her first major client came from a cold call and led her into institutional advisory work with nonprofits, boards, investment committees, and endowments. She discovered there was little competition for fiduciary-level advice that could bring different stakeholders into consensus.

Lori became one of the earliest major advisors to leave the wirehouse model and build an independent fiduciary firm. She did this right before and during the financial crisis, when the infrastructure for independence was still immature.

Her firm, LVW Advisors, evolved from a heavily institutional practice into a business serving institutions, nonprofits, health systems, and multigenerational families with complex wealth needs.

A major theme of the conversation is that AI will not replace the most human parts of financial advice. It will replace or disrupt advisors who only offer model portfolios, generic solutions, or technical work that machines can do better.

Lori believes the next era of wealth management belongs to teams that combine technology, multigenerational human empathy, customized advice, and in-person trust-building.

The deeper lesson: wealth does not live in a financial box. It lives inside families, institutions, emotions, transitions, children, businesses, loss, legacy, and human complexity.

Why You Should Listen

This ATOMIQ LEVEL conversation with Lori Van Dusen is not just a financial advisory interview. It is a story about a woman who began by selling copiers, entered Wall Street on Black Monday, became one of the only women in a room of hundreds, built a career by asking better questions, cold-called her way into major clients, pioneered institutional fiduciary advice, left the wirehouse world before the infrastructure was ready, and built an independent advisory firm around empathy, complexity, resilience, and trust.

It is about why the future of wealth management will not belong to generic model portfolios or advisors hiding behind technical jargon. It will belong to firms that understand people deeply, use technology intelligently, build multigenerational teams, and help clients solve the real problems beneath the financial questions.

It is about AI, but not in the usual way. Lori’s message is not that AI replaces the advisor. It is that AI gives great advisors more room to do what only humans can do: listen, interpret, empathize, read the room, build consensus, and guide families and institutions through decisions that matter.

It is about the great wealth transfer, but not as an abstract demographic statistic. It is about parents, children, spouses, heirs, boards, founders, nonprofits, health systems, and the human ecosystem where wealth actually lives.

Most of all, it is about grace.

Grace under pressure.

Grace after failure.

Grace in leadership.

Grace in transition.

Grace in the next step.

Press play on this conversation with Lori Van Dusen of LVW Advisors, connect with her on LinkedIn, visit LVWAdvisors.com, and read Running with Grace if you want the deeper story.

Because the future of wealth advice will not be won by the advisor who has the most data.

It will be won by the advisor who knows what the data means inside a human life.

The Human Future of Fiduciary Wealth

Before Lori Van Dusen became the founder and CEO of LVW Advisors, before she built one of the early independent fiduciary advisory firms to break away from the wirehouse model, before she became a Wall Street Journal bestselling author, before she was advising institutions, nonprofits, health systems, and multigenerational families through some of the most complex wealth decisions of their lives, she was selling copiers.

It sounds almost funny now, and Lori laughs at it too. Her first job was not on a trading desk or inside a polished private wealth office. It was selling office technology at a time when Japanese competitors were beating American companies on price and performance. The products she sold were more expensive and not always the best technology. That meant she could not win by reciting specs. She had to win by understanding people.

She had to walk into rooms where people did not necessarily want what she was selling and figure out what problem they actually had.

That was the first apprenticeship.

Not in finance. In listening.

Xerox trained her in Leesburg, Virginia, and gave her a framework that would quietly shape the rest of her life: SPIN. Situation. Problem. Implication. Need. It was a sales acronym, but in Lori’s hands, it became something deeper. It became a way of entering a conversation without assuming the answer. It taught her to understand the situation first, then the problem, then the implication of that problem, and only then the need.

Most people try to solve too soon. Lori learned to ask longer. That difference became her edge.

The Woman on the Trading Floor

After less than two years selling copiers, Lori moved to Wall Street. She had gone to Harvard, earned a graduate degree in education, and did not have a traditional finance background. When young people ask her today what kind of degree they need to enter finance, her answer is not the standard one. She did not begin with a finance degree. She began with work ethic, problem-solving, resilience, and the ability to connect with people.

She was hired by Lehman Brothers in the late 1980s, just as Lehman split into Shearson. She arrived in the World Trade Center as one of only two women in a class of about 300.

Then came her first day on the trading floor. Black Monday.

The market was crashing. People were screaming. Pandemonium filled the room. Lori, young and new and with no idea what a normal trading day was supposed to look like, leaned over to the man next to her and asked if this always happened.

It was the perfect beginning, in its own strange way. She had no business to lose. No legacy book to protect. No illusion that markets were always orderly. Her career in finance began with noise, panic, uncertainty, and volatility.

She learned early that the surface can collapse quickly. And if you are going to survive in finance, you need more than product knowledge.

You need composure.

The Real Problem Is Rarely the Presented Problem

Lori’s Harvard education reinforced something her sales training had already begun teaching her. In case study work, the problem as presented is rarely the real problem. People arrive with one version of what they think is wrong. Institutions arrive with another. Families arrive with another. Boards arrive with yet another.

But the surface problem is often only the doorway. The real work begins when you are willing to go deeper.

That requires comfort with discomfort. It requires asking questions other people avoid. It requires listening for what is not being said. It requires noticing when a committee member’s objection is not really about the investment policy, but about trust. It requires knowing that a family’s portfolio question may actually be a succession question, a control question, a fear question, a child question, or a marriage question.

Lori learned that if you want to solve meaningful problems, you have to stop trying to sell answers before you understand the human system around the question.

That is what SPIN became in her career. Not a sales trick. A human diagnostic.

Situation.

Problem.

Implication.

Need.

And in wealth management, the need is almost never just the portfolio.

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The Cold Call That Opened a New Market

Early in her Wall Street career, Lori landed a major client from a cold call. The family had sold a business to Unilever, and the relationship eventually introduced her to a much larger insight. The client told her that what she did for families was not being done in the institutional boards they served on. They were giving money away, sitting on boards, helping nonprofits, and watching organizations make financial decisions without the kind of integrated fiduciary guidance that Lori was providing.

So she began doing the same kind of advisory work for nonprofits. That move changed everything.

At the time, she found very little competition. There were plenty of people selling products, building portfolios, and trying to manage assets. But there were not many people walking into boardrooms as true fiduciary advisors, able to sit with investment committees, finance committees, and institutional leaders and help them understand the relationship between capital, mission, cash flow, governance, risk, and long-term needs.

A nonprofit endowment is technically a perpetual pool of capital, but if the advisor fails to understand the organization’s operating stresses, capital inflows, debt, regulatory risks, or potential need for a larger draw, that perpetual capital can suddenly become short-term capital.

Lori’s institutional work was never just about asset allocation. It was about understanding the organization. It was about the ecosystem around the money.

This is where her ability to drive consensus became essential. Boards are full of different people with different fears, priorities, experiences, and hills they are willing to die on. The best communication does not always happen in the boardroom. Sometimes it happens before or after. Sometimes it happens one-on-one. Sometimes the advisor’s job is not to win an argument, but to understand why people are not agreeing. That is not portfolio management. That is human leadership.

Leaving the Wirehouse Before the Road Was Built

Eventually, Lori saw that the wirehouse model could not fully support the kind of fiduciary work she believed clients needed. The solutions were too constrained. The technology was too limited. The systems did not talk to each other. Compliance was often built around policing the lowest common denominator rather than enabling sophisticated problem-solving for complex clients.

She believed wealth management was moving toward independence and fiduciary advice. So she left.

The timing was, on paper, brutal. She left what had become Smith Barney right before the Morgan Stanley merger and entered independence during the financial crisis with nearly a $6 billion practice. She thought she was late to the independent fiduciary movement. In reality, she was early.

And being early, as she says, often feels like being wrong.

The infrastructure was not there. The reporting was not right. The technology was immature. The road had not been built yet. She had the thesis, but the operating environment had not caught up.

That is one of the hardest forms of entrepreneurship. It is not being wrong about the future. It is being right before the market is ready to reward the truth. The conviction has to survive the missing bridges, missing tools, missing systems, and missing acceptance.

Lori survived it by building.

Over time, LVW Advisors became the kind of firm that could serve institutions and families not through a product shelf, but through a fiduciary model designed around complexity, objectivity, and trust.

Wealth Does Not Fit in a Neat Financial Box

Today, LVW Advisors serves institutions, nonprofits, health systems, and multigenerational families. The firm’s mix has evolved over time, with a larger share now focused on families and multigenerational wealth. But the core philosophy remains the same: understand the client’s real life before prescribing a financial answer.

The best-fit clients often have complicated lives. They may be navigating business transitions, family governance, children, legacy, philanthropy, liquidity, institutional obligations, health system pressures, or questions that do not fit neatly into a financial planning template.

Sometimes people need help with their children. Sometimes they need help stepping out of a business. Sometimes they need help deciding whether to stay in one.

Sometimes they need someone to understand that their spouse processes risk differently, or that a child may be affected by inheritance in ways that numbers cannot explain, or that the real challenge is not investment return but family alignment.

Not everything is an investment solution.

This is why Lori believes the future of advice is deeply human. Yes, technology can help. Yes, AI can analyze documents, summarize data, speed up technical work, and give advisors more time. But it cannot replace the human ability to read a room, build trust, detect nonverbal cues, uncover the unspoken problem, and help a family or board arrive at the decision they can actually live with.

AI can make advisors more productive. It cannot make shallow advice meaningful.

AI, Empathy, and the Return of the Human Advisor

One of the central themes of this conversation is the future of financial advice in the age of AI. Lori does not sound afraid of AI. She sounds energized by it. For the kind of firm she has built, AI is not a threat to the core value proposition. It is a tool that can remove friction, accelerate analysis, and allow the human team to spend more time on the deeper problems clients actually need help solving.

The advisory firms that should be worried are the ones built around generic model portfolios, one-size-fits-all solutions, and technical tasks that can be automated or commoditized. If the advisor’s value is primarily picking investments, producing reports, or delivering a standardized allocation, then AI and technology will compress that value.

But if the advisor’s value is human judgment, empathy, consensus building, family understanding, institutional context, proactive planning, and custom problem solving, AI becomes leverage.

It gives the advisor more time to be human.

That may be the great irony of this moment. The better the technology gets, the more valuable real human connection may become. In-person meetings may matter more, not less. Lori sees this already. The side conversations, the nonverbal cues, the family dynamics, the boardroom tension, the subtle signals that tell you what is really happening, those are difficult to capture through a screen.

People are still wired for companionship, trust, and understanding. Technology will change the tools. It will not eliminate the need to be known.

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The Multigenerational Team

When Lori thinks about the great wealth transfer and the future of advice, she does not believe the answer is simply better software. She believes the advisory firm itself has to become multigenerational.

If the client is multigenerational, the advisory team should be too.

A founder in her sixties or seventies may relate to one advisor. A twenty-something heir may relate to another. A spouse who wants high-touch in-person meetings may need something different from a next-generation family member who wants a digital portal, real-time chat, and answers at 2 a.m. The point is not to force every client into one model. The point is to meet each person where they are.

That is hard to build because it is custom. It requires people, process, technology, empathy, and an understanding that wealth does not live in a parallel universe. It lives inside the ecosystem of the person or institution.

Lori believes one of LVW’s strengths is that it has built a multigenerational team capable of serving clients across different touchpoints and communication preferences. That is the future she sees: a firm where technology makes personalization easier, not more sterile; where AI supports the back end, but humans remain at the front of trust; where the client experience becomes richer because the firm is not trapped in legacy systems or one-size-fits-all assumptions.

The winning advisory firm of the next era will not merely manage money. It will organize human complexity.

Building a Business That Can Live Beyond the Founder

Another powerful thread in Lori’s story is her commitment to building a business that can operate without her. She describes it as a lifelong mission, especially after having children. She wanted to mentor people, coach them, teach what she knew, build processes, stress test the firm, and identify vulnerabilities before they became problems.

1. What happens if something happens to a key person?

2. Where is the business fragile?

3. What does the team know that only the founder used to know?

4. How does the firm continue to serve clients if the founder steps back?

These are the questions real founders eventually have to face. Lori has not waited until the end of her career to ask them. She has built around them. She jokes that she is now “useless overhead” because the business runs without her, but behind the joke is a serious achievement. A founder who can step out of the day-to-day has created something more valuable than a practice.

She has created an enterprise.

That frees her to operate at 30,000 feet, thinking about strategy, people, process, technology, and where the firm needs to be over the next five years. That may be her highest and best use now. Not because she loves clients less, but because the next era of advisory work requires intentional design.

The firm has to be architected for what is coming.

Running with Grace

Lori’s book, Running with Grace, came out of the same human philosophy that runs through this conversation. She did not initially set out with some grand author plan. But the stories came together, and the book became a way to pay forward experiences that might help others navigate failure, loss, resilience, and the imperfect reality beneath externally successful lives.

One of the central ideas is simple: Put one foot in front of the other.

That sounds almost too basic until life becomes overwhelming. Then it becomes everything. In business, in grief, in markets, in parenting, in leadership, in failure, in reinvention, sometimes the only real strategy is the next right step.

Lori speaks openly about failure and loss, not as branding exercises, but as life material. She would not want to repeat some of what she has lived through, but she has learned from it. She believes people need to examine failure rather than simply move on, because if you do not perform the post-mortem, you repeat the pattern.

This is not just useful for business. It is useful for families. It is useful for relationships. It is useful for leadership. The point is not to avoid every fall. The point is to become the kind of person who learns how to rise.

The real risk is doing nothing!

~Chris J Snook

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The Hidden Architecture Beneath Global Markets

, known as Mr Tix, brings the kind of macro lens that is increasingly rare: credit-first, historically grounded, globally informed, and willing to look past the headline narrative to ask what the debt, collateral, energy, currency, and political incentives are actually saying.

His work sits at the intersection of macroeconomics, credit markets, geopolitics, gold, emerging markets, sovereign risk, and the uncomfortable reality that most investors still underestimate:

Without credit, there is no macro.

Subscribe to Macronomics-Mr Tix if you want a sharper view of the forces reshaping capital, currency, energy, Europe, China, and the next phase of global market risk.

TL:DR Key Takeaways

Martin Tixier’s worldview was shaped early by international exposure, bilingual education, and friendships across cultures, religions, and countries. That global lens later became central to how he interprets markets.

His father was not in finance, but helped shape Martin’s intellectual foundation by pointing him toward classical economic books. Jacques Rueff’s The Monetary Sin of the West, Angus Maddison’s work on world economic history, Gavekal Research, James Goldsmith’s The Trap and The Response, and Maurice Allais all helped frame his view of money, trade, globalization, and the cost of policy mistakes.

Martin’s career began in trading rooms and credit markets, including work at Bank of America in London, where Anthony Peters became a mentor. His experience selling investment-grade bonds, high-yield, asset-backed securities, and credit products to family offices, asset managers, hedge funds, and bank loan books taught him that credit is the real heartbeat of the economy.

One of the central ideas in this conversation is the “money illusion.” Martin argues that the U.S. equity market’s long-term rise since 2007 tracks closely with the growth of U.S. national debt. In plain English: a lot of what investors experience as market wealth may actually be debt-driven liquidity expansion.

Martin believes something broke in 2022, especially after the Russia-Ukraine war and the seizure of Russian central bank reserves. In his view, U.S. Treasuries lost part of their safe-haven aura because the world saw that reserves could become politically conditional.

Gold, in Martin’s framework, is not just an asset. It is a benchmark and a thermometer for the value of money. Investors should ask whether the assets they hold can outperform gold over meaningful time horizons.

Martin sees stagflationary pressure building because war is inflationary, sovereign yields are rising, and long-term interest rates are increasingly governed by fiscal discipline, not just central bank policy.

He argues that productive debt, such as Eisenhower’s interstate highway system, can strengthen a nation, while unproductive debt creates fragility. In today’s AI race, he sees energy infrastructure, grid capacity, gas turbines, copper, nuclear, and data center inputs as critical strategic bottlenecks.

On China, Martin does not believe real decoupling from the U.S. is possible. The U.S. needs Chinese supply chains for energy infrastructure and data centers. China needs the U.S. market. A grand bargain may be more likely than a clean break.

Europe, in his view, has scientific talent but is politically weakened by leadership failures, over-centralization, lack of democratic mandate, and delayed structural reform. Countries like Portugal, Spain, Ireland, and Greece took painful medicine. France, he argues, has postponed it.

On emerging markets, Martin is particularly interested in country-by-country opportunities, with Brazil standing out because of high real rates, cheap equity valuations, and potential currency and rate tailwinds.

The deeper message: investors need to stop looking only at equity prices and start understanding credit, fiscal discipline, energy, currency risk, geopolitics, and gold-relative returns.

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Meet -”Mr. Tix”

Before Martin Tixier became Mr Tix of Macronomics, before his Substack began rising among readers hungry for sharper macro insight, before he started translating credit markets, gold, fiscal discipline, geopolitics, China, Europe, and emerging markets into a framework investors could actually use, he was a boy in France being taught to see the world as larger than the country he was born into.

His parents put him in a bilingual school when he was five years old. That one decision mattered. It placed him early in a world of different languages, cultures, religions, nationalities, and assumptions. He grew up around people from everywhere, and those friendships became more than childhood memories. They became part of his operating system.

Martin did not learn macro first from a chart. He learned it from people. When you grow up around different cultures, you learn that no nation is the center of the story forever. You learn that money, trade, institutions, power, and trust are interpreted differently depending on where someone stands. You learn that history does not belong to one country, one market, or one currency. It moves across borders, and so does capital.

That early international exposure became the seed of a career spent reading the world through the lens of credit, history, and monetary architecture.

The Father Who Pointed Him Toward the Books

Martin’s father was not a finance professional. But he gave his son something more valuable than a job referral or a market tip. He pointed him toward books.

Classical economic books.Hard books.

Books that force the reader to think beyond headlines and quarterly market narratives.

One of the most important was Jacques Rueff’s The Monetary Sin of the West, a book that helped shape Martin’s understanding of monetary systems, credit pyramids, debt, and the illusion that nominal wealth always means real prosperity. He later discovered Gavekal Research around 2005 and 2006, through prop traders at Bank of America, and began reading deeply about asset allocation and macro. He read Angus Maddison’s sweeping work on the world economy from year zero to projections into 2030. He read Sir James Goldsmith’s The Trap and The Response, books from the early 1990s that warned against the naive globalization consensus before the consequences were obvious.

Those books mattered because they trained him to see today’s market conditions as part of a longer arc.

Goldsmith, in particular, warned that opening the world too aggressively without regard for local communities, industrial bases, and national cohesion would eventually destroy domestic resilience. At the time, that sounded unfashionable. Today, with reshoring, tariffs, supply chain anxiety, industrial policy, and strategic competition with China back at the center of the conversation, it sounds less like nostalgia and more like prophecy.

Martin’s intellectual foundation was built on a simple idea:

The warnings were there. Most people just ignored them until the bill came due.

The Credit Education

Martin’s professional career took him into trading rooms, credit desks, and the machinery of global finance. He studied at ESSEC BBA in France, pursued international exposure, and took an early internship in Geneva as an assistant trader focused on Japanese bonds issued in French francs. From there, he moved through internships in trading rooms and eventually to London, where he worked at Bank of America.

That is where he met Anthony Peters, who became a mentor. It was also where Martin’s credit-first worldview hardened.

He worked as a flow credit salesperson, selling investment-grade bonds, high-yield bonds, asset-backed securities, and other credit products to a wide range of clients: family offices, asset managers, hedge funds, and bank loan books. It was a front-row seat to how money really moves through the system, not as a theory, but as a daily negotiation between borrowers, lenders, risk managers, traders, portfolio managers, liquidity, and fear.

Equities may get the attention.

Credit tells you when the floor is cracking.

Martin is clear on this point: credit is the heart of the economy. Without credit, there is no macro. Equity markets are visible and emotionally seductive, but they are small relative to credit. If you want to understand the real picture, you have to understand debt, lending, spreads, refinancing, collateral, and the cost of capital.

He saw that lesson in real time during the financial crisis. He was at Bank of America as the credit markets began sending warning signals long before equities fully understood what was coming. The layoffs came in waves. Anthony Peters was part of the first wave. Martin was part of another. But the market lesson stayed with him.

Credit saw the crisis first. That is why credit people never look at markets quite the same way again.

The European Crisis and the Memory of 2011

After London, Martin spent years in Brussels, beginning in 2011, just as the European sovereign crisis was reaching a dangerous point. To casual observers, the Eurozone crisis may now feel like old news. To people who lived inside the system at the time, it was a near-death experience for the European banking sector.

Martin remembers how close Europe came to a collapse. He remembers the credit default swap spreads blowing out across financials. He remembers the stress in senior and subordinated bank debt. He remembers the ECB stepping in with long-term refinancing operations. He remembers the Fed helping the ECB through dollar swap lines.

These are not academic memories. They are part of the reason he watches sovereign yields, credit spreads, bank funding, and fiscal discipline with such intensity.

Because when credit breaks, the polite language disappears.

Suddenly, the question is not whether the market is expensive or cheap. The question is whether the system can fund itself tomorrow.

The Money/Wealth Illusion

One of the most important ideas Martin brings into this conversation is the “money illusion.” It comes through the influence of Jacques Rueff and Martin’s own credit-market lens.

He gives a simple example. If you start in January 2007 and look at the compounded annual growth rate of the S&P 500, it has been roughly around 8%. If you compare that with the compounded annual growth rate of U.S. national debt over the same period, he argues that the growth rates are remarkably similar.

The implication is uncomfortable.

What many investors experience as equity market wealth may be tied to the expansion of debt.

That does not mean companies are fake. It does not mean profits do not matter. It does not mean innovation does not matter. But it does mean nominal asset gains can be deeply entangled with the debt machine underneath the economy.

When liquidity is created, it has to go somewhere. It flows into scarce assets, productive assets, winner-take-all assets, real estate, equities, Bitcoin, gold, private markets, and whatever the system decides can absorb excess capital. If enough money piles into the same assets, prices rise, narratives harden, and people begin mistaking liquidity-driven gains for pure genius.

That is the money illusion.

It makes people feel wealthier, but the question is whether their wealth is rising faster than the debasement of the money they measure it in.

Gold as the Thermometer

For Martin, gold is not merely a commodity, a relic, or a fear trade. It is a benchmark. It is a thermometer for the value of money. It is a way to ask whether your portfolio is actually preserving purchasing power or simply rising in nominal terms alongside the debt machine.

He argues that investors should increasingly compare their equity performance against gold over one-year, three-year, and five-year periods. If an equity cannot outperform gold through a meaningful cycle, then the investor has to ask what they really own and why.

That is a different kind of benchmark than the one most advisors use. The standard investor compares a stock to an index, a portfolio to a 60/40 model, or a manager to a peer group. Martin’s lens asks a more primal question:

Did you actually outrun monetary debasement?

This becomes especially important if we are entering a more stagflationary world. War is inflationary. Energy constraints are inflationary. Supply chain fragmentation is inflationary. Rising sovereign yields increase the price of capital. Long-term rates become less about central bank wishes and more about fiscal discipline.

In that world, gold becomes a message. Ignore it at your own risk.

What Broke in 2022

Martin believes something changed in 2022. The Russia-Ukraine war was not just a geopolitical event. It marked a deeper shift in how the rest of the world perceived U.S. Treasuries, dollar reserves, and the safety of Western financial custody.

In his view, the United States made two major strategic mistakes. The first was weaponizing the dollar through sanctions and financial pressure. The second was pushing Russia closer to China. Russia is one of the world’s largest commodity players. China is the world’s largest industrial producer. Geographically, strategically, and economically, the match is powerful.

Then came the seizure of Russian central bank reserves. To Martin, that sent a chilling message to the rest of the world:

If you fall out of favor, your reserves may not be yours.

That realization accelerated the desire among central banks and sovereign actors to hold more gold. It changed the perception of Treasuries as a politically neutral safe-haven. It made reserve managers rethink what safety means in a world where finance is increasingly used as a geopolitical weapon.

For investors, this is not just a foreign policy debate. It is an asset allocation question. If the world begins reassessing the safety of dollar collateral, the effects ripple through gold, Treasuries, currencies, commodities, emerging markets, and every portfolio built on old assumptions.

Productive Debt Versus Destructive Debt

Martin is not anti-debt in some simplistic sense. He makes an important distinction between productive and unproductive debt.

Productive debt builds the future. Eisenhower’s interstate highway system is an example. It strengthened commerce, mobility, logistics, productivity, national defense, and the physical structure of the American economy. It was debt that created long-term capacity.

Unproductive debt props up consumption, political promises, misallocated spending, fraud, waste, and short-term power games. It can create the illusion of prosperity while weakening the foundation beneath it.

That distinction matters today because the United States, Europe, and China are all making enormous choices about infrastructure, energy, defense, AI, and industrial capacity. The question is not only how much debt a country issues. The question is what the debt builds.

Martin’s view is blunt: economic output is energy transformed.

That sentence brings the AI debate back to earth. Everyone talks about models, chips, data, and software. But AI at scale needs electricity, grids, gas turbines, copper, nuclear, renewables, transmission, substations, and data centers. China has spent massively on infrastructure, the electric grid, nuclear, solar, renewables, and industrial capacity. The U.S. still leads in frontier innovation, but it faces real bottlenecks in energy infrastructure.

The future of AI may not be decided only by who writes the best model. It may be decided by who can power it.

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China, the U.S., and the Grand Bargain

One of the most important parts of this conversation is Martin’s refusal to accept simplistic U.S.-China decoupling narratives. The two countries are rivals, but they are also deeply entangled. The U.S. needs Chinese supply chains for data center inputs, gas turbines, copper components, and other industrial necessities. China needs the U.S. market and the broader global system.

There is no clean separation. There may need to be a grand bargain.

Martin frames the emerging world as a new Yalta-like moment, with the United States, China, and Russia as the major players. Europe, in his view, has become increasingly irrelevant in this power conversation, not because it lacks talent or science, but because its political leadership has weakened its strategic position.

China’s strengths are obvious: scale, infrastructure, industrial capacity, long-term planning, supply chain control, and a massive pool of engineers. But Martin also highlights its vulnerabilities, especially capital flight. He describes the Great Wall of China not only as facing outward, but inward. Capital controls help hold the system together because many Chinese citizens would otherwise prefer to move capital abroad.

China’s leadership understands this. It prizes harmony and balance above almost anything else because managing 1.3 billion people is not easy. Every five to ten years, it conducts corruption purges and mini-resets to keep excesses from destabilizing the system. Martin notes that you can even see traces of these cycles in luxury goods and high-end cognac sales when anti-corruption campaigns reduce conspicuous gifting and elite spending.

That is the kind of macro detail Martin watches. Not just GDP.

But Cognac sales!

Because sometimes the luxury cycle tells you what the political cycle is doing.

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Europe’s Delayed Reckoning

Martin’s assessment of Europe is not sentimental. He believes Europe still has serious scientific and intellectual capability, but its political class has become a major obstacle. He is critical of the centralization of European power in institutions and leaders without a clear democratic mandate. He sees declining popularity, leadership turnover, and falling political credibility across the continent.

Some European countries have already taken painful medicine. Portugal, Spain, Ireland, and Greece went through difficult structural reforms after the crisis forced their hand. Portugal, in particular, now stands out in Martin’s mind because fiscal discipline has allowed it to borrow more cheaply than France on the long end of the curve.

That is a remarkable reversal.

The bond market is telling a story.

France, by contrast, has postponed structural reform. Martin argues that, eventually, France will have to go line by line through spending and decide what stays and what gets cut. There is no painless way around delayed discipline.

Fiscal discipline matters because long-term interest rates are not ultimately controlled by speeches from central bankers. Central banks can influence the short end of the curve. The long end answers to trust, debt, deficits, inflation expectations, and fiscal credibility.

Portugal has learned that lesson. France still has to face it.

The Emerging Market Lens

Martin does not treat emerging markets as one big basket. He looks country by country, structure by structure, and credit condition by credit condition.

Brazil stands out to him. His reasoning is credit-driven and simple. If rates are extremely high relative to inflation, and the real rate is strongly positive, then there may be a compelling opportunity if rates eventually come down. Add cheap equity valuations and a stronger currency trend, and the setup becomes interesting.

He does not claim emerging markets are universally attractive. He does not say to buy everything outside the U.S. But he does believe investors should look beyond the standard U.S.-centric allocation model, especially if the dollar weakens and country-specific opportunities emerge.

He also sees enormous long-term importance in India, Indonesia, Vietnam, Southeast Asia, and the broader eastward shift of economic gravity. Drawing on Angus Maddison’s historical work, he reminds listeners that China and India were once dominant forces in global trade and economic output. The world moving east is not an anomaly.

It may be a return.

Derivatives, Options, and the Casino Mood

Later in the conversation, Martin turns toward market structure and risk. He does not overstate the derivative danger in a simplistic way, acknowledging that reforms after the Great Financial Crisis, including trade compression, reduced some notional risks. But he is concerned about the explosion of very short-dated options activity, 0DTE-style trading, and the broader casino mood in markets.

He sees echoes of the Roaring Twenties: intense speculation, betting platforms, short-term options, crypto Ponzi behavior, record M&A, record debt issuance, and rising dispersion across equities and credit.

Those are not always immediate crash signals. But they are cycle signals.

The casino phase often arrives when liquidity, leverage, confidence, and speculation have already done their work. The question becomes not whether the party is loud, but whether the credit cycle is quietly turning underneath the noise.

Again, Martin comes back to credit. Because credit usually whispers before equities scream.

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Why You Should Listen

This ATOMIQ LEVEL conversation with Martin Tixier is not just another macro interview. It is a guided walk through the architecture beneath global markets with someone who has spent his life reading across cultures, histories, balance sheets, credit markets, sovereign crises, central bank actions, and geopolitical fractures.

It is about a boy in France who learned English at five and grew up among international classmates before becoming a credit-market thinker shaped by classical economics, monetary history, Bank of America trading rooms, Anthony Peters, Gavekal, Jacques Rueff, Angus Maddison, James Goldsmith, European crisis, and the hard lesson that credit sees trouble before equities admit it.

It is about the money illusion hiding beneath the S&P 500, the idea that debt growth and equity growth may be more connected than most investors want to believe. It is about why gold may be a better benchmark for real wealth preservation than nominal index performance. It is about why 2022 changed how the world thinks about reserves, Treasuries, sanctions, and safety. It is about why productive debt builds infrastructure while unproductive debt builds fragility.

It is also about power. U.S. and China. Russia and commodities. Europe’s political weakness. Brazil’s real-rate opportunity. India’s potential. China’s inward-facing capital controls. Portugal’s fiscal discipline. France’s delayed reckoning. AI’s energy bottleneck. The coming importance of data centers, grids, gas turbines, copper, and nuclear power.

Most investors are still trained to watch equities first.

Martin Tixier is telling you to watch credit, gold, fiscal discipline, energy, and history.

That is why this conversation matters. It connects the dots between money, debt, geopolitics, infrastructure, and portfolio survival in a world that is no longer governed by the assumptions of the last 30 years.

Press play on this ATOMIQ LEVEL conversation with Martin Tixier, aka Mr Tix of Macronomics, and you will hear a macro thinker who does not just ask where markets are going next.

He asks what kind of world is being financed underneath them.

Because in the end, markets may rise, currencies may weaken, politicians may spend, central banks may intervene, and investors may chase whatever is working.

But credit remembers. Gold remembers. History remembers.

And the investors who learn to read all three may be the ones best prepared for what comes next.

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The real risk is doing nothing!

~Chris J Snook

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