The people who bought the excitement lost money before lunch.

But retail buyers were not the story of Friday…it was the employees of SpaceX.

An estimated 4,000 employees became millionaires at the opening bell, including welders and cafeteria cooks who took stock instead of bigger paychecks a decade ago. Roughly 400 of them are now worth $100 million or more.

I want to sit with that for a second, because it contains the entire lesson of this article. Those employees just finished a trade they entered ten years ago at private prices. Anyone who bought the open on Friday started a trade at the exact moment thousands of informed insiders finally got permission to sell.

Warren Buffett has thought about this asymmetry longer than most of us have been investing. His conclusion:

“It’s almost a mathematical impossibility to imagine that, out of the thousands of things for sale on a given day, the most attractively priced is the one being sold by a knowledgeable seller to a less-knowledgeable buyer.”

Asked in 2019 whether he’d buy the Uber IPO, he noted that in 54 years he didn’t think Berkshire had ever bought a new issue. At Berkshire meetings he’s put it more bluntly: the sellers pick the timing, so a new issue isn’t worth five seconds of your attention.

Strong words. Let’s test them against the evidence.

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The structure of the trade

Let’s think about what an initial public offering actually is for a moment.

• A group of insiders who know the business better than anyone alive chooses the precise moment to sell you a piece of it.

• They hire 21 banks to market it.

• They time it for maximum enthusiasm.

• Then the shares open for trading at whatever price the most excited buyer in America will pay that morning.

Ben Graham flagged this in The Intelligent Investor decades ago: new issues come to market under conditions favorable to the seller, which by definition makes them less favorable for the buyer. His student just said it with more color.

The modern data backs them both.

Edward Jones and FactSet studied the 30 largest IPOs of the past 20 years and found that, measured from the first traded price rather than the offer price, the average return was negative 1.4%, with the group lagging the S&P 500 through its first year.

Jay Ritter’s research at the University of Florida shows unprofitable IPOs pop 26.5% on day one and then return negative 0.5% over the next three years, trailing the market by more than 30 percentage points.

The pop is real.
It just isn’t for you.

It goes to the institutions who received allocations at the offer price, a price you were never going to get.

Two receipts from the past year

Figma priced its July 2025 IPO at $33 and closed its first day at $115.50, a 250% gain celebrated everywhere as proof the IPO market was back. Retail investors buying that open paid $85 or more. The deliberately low pricing triggered a performance clause that released insider shares after just 36 days instead of 180. Today the stock trades near $21, down more than 80% from its peak and below the original offer price. The business itself is fine, with revenue up 41% last year.

The entry price was the problem.

BitGo, the digital asset custodian, priced at $18 in January, popped about 25% on debut, and fell below its offer price by the second trading session. It now sits more than 40% below where it priced, to the point where analysts have shifted from growth stories to takeover speculation.

• Two real companies.

• Two functioning businesses.

• Two groups of early investors who exited beautifully, and

• Two groups of open-market buyers who funded the exit.

The pipeline deserves the same lens

The next twelve months bring Anthropic and OpenAI, both confidentially filed, plus expected listings from Kraken and Securitize. These are serious companies, and nothing here predicts they fail.

The Buffett model doesn’t say new public companies are bad businesses, but rather that the moment of listing is structurally the worst-informed, most-hyped, seller-optimized moment to buy them.

Consider what these filings represent. Anthropic’s last private round valued it at $965 billion. OpenAI’s at $852 billion. The venture funds, sovereign wealth funds, and employees who own those shares have watched their stakes appreciate at rates Forge Global measures at 65.7% annually for recent unicorns during their private years. The IPO is how that decade of private gains becomes spendable money. The word “offering” describes their side of the transaction, not yours.

Even Buffett’s lone modern exception proves the point. When Berkshire bought into Snowflake’s 2020 IPO, it paid the $120 offer price. Retail’s first available price that morning was roughly double that. Same day, same stock, two different trades.

The Buffett Framework Question: Would you buy a private business from its founder on the one day he chose to sell, at a price his hired marketers spent six weeks promoting, while thousands of other businesses sit on the shelf at prices set by ordinary daily auction? If not, what makes a ticker symbol different?

Where the five seconds are better spent

Here’s the part of Buffett’s model people skip. He isn’t telling you to sit in cash. He’s telling you the auction market, with its thousands of existing companies priced by daily supply and demand rather than roadshows, is where bargains actually appear, usually wearing bad headlines.

Cracker Barrel is a fresh example. Last August a logo redesign turned the company into a culture-war punching bag and the stock got left for dead. The restaurants kept serving food and generating cash the entire time. This week the company reported earnings that tripled net income year over year and beat estimates by a wide margin, and the stock jumped nearly 30% in a single day. It’s now up more than 67% this year.

The investors who got paid weren’t the ones chasing a hyped debut, but the ones willing to look at an unloved business while everyone else looked away.

To be clear, I’m not recommending Cracker Barrel, and after this week’s move much of that easy money is gone. The point is the pattern.

Opportunity in public markets tends to come from other people’s overreactions, and overreactions cluster around boring, disliked, or embarrassing situations. They almost never cluster around the most marketed security in the world on its first day of trading.

Where I could be wrong and the Watchlist…

Fairness requires the other side. Facebook fell more than 50% in its first 18 weeks and went on to return over 1,600% for patient holders. Amazon lost most of its value after 2000 and became the buy of the decade anyway. If the AI buildout compounds the way bulls project, today’s prices will look quaint, and the day-one buyers will look prescient rather than impatient. Buffett’s model manages the odds, not the certainty.

Some IPOs work.
The data just says you shouldn’t expect yours to be the one that does.

1. SpaceX’s first earnings call as a public company, expected in July, with a rumored early lockup window two days after it.

2. Nasdaq-100 inclusion around July 7 and the mechanical index buying that follows.

3. Anthropic and OpenAI’s public S-1 filings, where the real financials replace the leaks.

4. Kraken and Securitize listing timelines as the crypto IPO window stays open.

5. Whether Figma and BitGo find their footing, the best live experiment on post-IPO price discovery.

The biggest IPO in history will still be there in six months, with public earnings reports and a lockup expiration behind it. Buffett wouldn’t spend five seconds on it today. The auction market is open all year.

Moving right along…

This Week In 2 Minutes

“How to Go From Idea to Usable Tool With AI in a Weekend” (June 9)

This past weekend I built a free Series 7 math trainer, and I never wrote a line of code. Three tools did the work in a chain: Claude Code as the engineer, GitHub as the filing cabinet, Vercel as the launchpad. I describe what I want, it builds and ships.

The tool is the least interesting part. What matters is that the cost of building the exact thing you need has dropped close to zero, so the bottleneck isn’t money or engineers anymore. It’s whether you notice a problem and reach for the tool.

The method runs in five steps: pick a real problem you already have, gather your raw material, describe the outcome instead of the code, work in short test-and-correct loops, and be the judge of whether the result is any good. That last step is the moat. Domain expertise is what lets you catch the model when it puts a formula in wrong, which means AI replaces the tedious work sitting under your judgment, not the judgment itself.

Read the full article here.

1,000 Advisors, $28 Trillion in AUM, and Only 1 Crypto Panel (June 12)

I spent this week at Wealth Management EDGE in Boca Raton, the largest gathering of senior RIAs in the country. Last year digital assets had a main-stage slot. This year it was one panel and one booth.

The conversation didn’t shrink so much as change shape. Crypto as an asset class got quieter while tokenization as infrastructure got louder, and private markets and AI dominated every track in the building.

The session that hit closest to home was Puerto Rico’s Act 60 regime, roughly 4% tax versus about 41% in Florida or 52% in New York City, now extended through 2055. That’s the structure I’m building around with a new RIA. The cautionary tale was a CoinShares altcoin-basket ETF down around 70% since October, with 0.96 correlation to Bitcoin and a near-1% fee. You get Bitcoin’s volatility, none of the diversification, and a bill on top.

Read the full article here.

This Week’s Winners 🏆

• Cracker Barrel (CBRL). The boring-stock-bounces-back trade of the week. After a logo controversy left the stock for dead last August, Monday’s earnings tripled net income year over year and beat estimates badly enough to send shares up nearly 30% in a session. It’s now up more than 45% on the year. The lesson isn’t the chain itself, but that opportunity hides in disliked, unglamorous names while everyone stares at the launch pad.

• SpaceX employees (all 4,000 of them). The biggest IPO in history minted an estimated 4,000 millionaires at Friday’s open, roughly 400 of them worth $100 million or more, including welders and cooks who took stock over salary a decade ago. A group of 100+ even built their own low-fee wealth management vehicle to handle the windfall. This is what winning an IPO actually looks like, and notice it has nothing to do with buying the open.

• Cash on the sidelines. With roughly $8 trillion parked in money market funds and a 2026 IPO calendar that could demand north of $200 billion, dry powder is quietly the strongest position in the market. Patience is an asset that pays you to hold it right now. The investors with cash get to be buyers on their own terms instead of someone else’s exit.

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…and Losers 📉

• Anyone betting on a June rate cut. The setup flipped on bulls. May CPI came in at 4.2% year over year, well above the Fed’s 2% target, while the economy added 172,000 jobs and unemployment held at 4.3%. With inflation surging and the labor market healthy, the textbook next move is a hike, not a cut, and the risk now is a Fed bias shift from easing toward tightening. Rate-cut hope has been the market’s crutch all spring, and this week’s data kicked it out.

  

• Crypto longs into the macro print. Digital assets traded defensively ahead of the Fed. Bitcoin’s pullback added pressure before the meeting, with the broad crypto drop signaling investors hedging out risk ahead of the policy decision. Rate expectations drive liquidity, risk appetite, and institutional positioning, which is why crypto reacts sharply to the Fed. When the discount rate is the swing factor, the most rate-sensitive assets get sold first.

• Oversupply bears caught offside. The 2026 glut narrative ran into reality. A Reuters poll had Wall Street modeling WTI averaging around $59 for 2026 on China demand worries and rising OPEC supply, then geopolitics intervened and the IEA actually dialed back its oversupply warning after winter shocks. Anyone short energy on the glut thesis spent the week watching the opposite play out. Consensus positioning is most dangerous exactly when everyone agrees.

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What to Watch For This Week 👀

• SpaceX’s first index-inclusion wave (~July 7 setup). The mechanical story beats the narrative one. About 15 trading days after listing, SpaceX qualifies for the Nasdaq-100, triggering forced buying from every index fund that tracks it, with estimates running into the tens of billions. Watch whether that artificial demand props the stock or simply gives early holders a cleaner exit.

• The next crypto S-1. With the IPO window open, watch for Kraken, Securitize, or another digital asset name to file. Each filing is a free look at real financials replacing years of private-round leaks. The terms they choose, lockup length, retail allocation, gross vs. net revenue accounting, will tell you how confident these companies actually are.

• The Fed meeting and the dot plot. The June FOMC decision and updated projections land this week, and with rate-cut expectations getting repriced all spring, the dot plot matters more than the decision itself. Every IPO valuation in the pipeline, from OpenAI to Anthropic, is ultimately a bet on the discount rate. Cheaper money inflates these numbers; tighter money deflates them.

  

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Matthew Snider is the founder of Block3 Strategy Group, author of “Warren Buffett in a Web3 World,” and publisher of the BitFinance newsletter. He holds a Series 65 and MBA, and has been an active participant in digital asset markets since 2015. This article is for educational purposes only and should not be considered financial advice. Always consult with a qualified professional before making investment decisions.

Sources

1. Edward Jones & FactSet, “Don’t Let Mega IPO Buzz Cloud Your Judgment”

2. Jay R. Ritter, University of Florida

3. Warren Buffett, CNBC interview, May 2019

4. University of Berkshire Hathaway (Pecaut & Wrenn)

5. Benjamin Graham, The Intelligent Investor

6. Fidelity Investments, “SpaceX IPO Explained”

7. Bloomberg, November 2025 — Figma shares falling below IPO price

8. InvestorPlace via TradingView, February 2026

9. FinTech Futures and Cointelegraph, January 2026

10. Forge Global, “Late-Stage Private Companies: The New Growth Investing”

11. Goldman Sachs Research — 2026 U.S. IPO volume projections; “25 Years On: Lessons from the Bursting of the Technology Bubble”

12. Cracker Barrel Old Country Store, fiscal Q3 2026 earnings release, June 2026; Fast Company and Investing.com coverage

I didn’t go to talk about crypto. I went to talk about the future of finance, and that distinction matters more than ever. This conference proved it.

Here’s what I saw, what I heard, and what I think it means.

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The Room Has Changed

Last year, digital assets had a main stage slot at EDGE. Multiple firms showed up and there was solid crypto energy.

This year? One panel. One booth. That was the entire digital asset footprint at a conference with over 250 speakers.

You can read that two ways.

• The bearish read says the market is in a slump, prices are down, and advisor interest evaporated with the chart. Fair enough. The audience questions at the lone crypto panel mostly boiled down to “why is Bitcoin down?” That tells you where heads are at.

• The bullish read, and the one I left with, is that the conversation didn’t shrink so much as change shape. Crypto as an asset class got quieter while tokenization as infrastructure got louder. (More on that at the end.)

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The RIA of the Future Runs on Private Markets & AI

The dominant themes of the week were unmistakable: Private markets and AI.

Every summit track, every vendor booth, every hallway conversation orbited one of those two suns.

The opening keynote from Sanctuary Wealth’s Patrick McGowan walked through H1 2026 capital flows from the wealth channel into private assets including private equity, private credit, real estate, infrastructure.

The framework on screen said it plainly: rotation, risk, reset, re-entry.

Advisors aren’t asking whether to allocate to private markets anymore.
They’re asking how to do it operationally.

That operational question is real. One session laid out the hidden time burden with no spin. Private markets aren’t “Schwab click and drop.” Enhancements to the process were related to automated subscription docs, capital call management, cash reserves, ongoing monitoring, and reporting across multiple custodians with different formats and data quality.

The vendors filling that gap, names like Arch, InvestCloud, and Gridline, had real traffic at their booths.

On the AI side, sessions on designing the AI-enabled firm of the future made one thing clear: AI is no longer an experiment in wealth management; it’s becoming the operating layer.

Firms are making governance and data decisions now that will determine who compounds advantage over the next decade. Zoe Financial’s Andres Garcia-Amaya made the case that AI supercharges operational efficiency and personalizes the client experience for growing RIAs.

I agree, and this is the thesis I run my own businesses on. AI as the orchestration layer, not the replacement layer. The firms that get this will pull away, while the firms that wait will spend the next five years explaining why their margins shrank.

Puerto Rico Stole the Show for Me

The session that hit closest to home was a presention on Puerto Rico as the best tax jurisdiction available to U.S. citizens.

For my geographically challenged readers, here is where Puerto Rico is on a map. And yes, it’s part of the United States, uses the U.S. Dollar and only requires an ID to enter.

This topic resonated deeply with me as it’s something I’m working to build right now with Colton Alexander Advisers, a new Puerto Rico-based registered investment adviser designed around the island’s structural advantages. I sat in that room with more than professional curiosity.

The numbers aren’t subtle.

Act 60 provides a maximum 4% tax on interest, dividends, and capital gains for bona fide resident investors. There’s also a 4% corporate rate on exported services, which covers asset management, law, software, and consulting, with dividends from those activities tax free. In March, Act 60 was extended through 2055. That’s thirty years of tax certainty, signed into law.

Compare the rates. Roughly 4% in Puerto Rico versus about 41% in Florida and 52% in New York City. The presentation ran the compounding math, and I recreated it below because numbers you can check beat adjectives.

A $10 million portfolio growing at 20% for 30 years becomes roughly $1.9 billion after tax in Puerto Rico. The same portfolio in New York City ends around $161 million. That’s a $1.8 billion difference. Even against zero-income-tax Florida, the gap is about $1.7 billion.

Here’s the part people miss. None of this is offshore, because Puerto Rico is a U.S. territory with federal courts and FDIC banking in dollars. No passport changes, no expatriation tax, no currency risk, no renunciation of citizenship. It’s the only jurisdiction on earth that offers this treatment to U.S. citizens who keep their passport.

I think Puerto Rico is the most underpriced opportunity in American wealth management. The advisors in that room were paying attention, and the smart ones will act.

Tokenized Real Estate and the Happy Hour Test

Some of the best conversations at any conference happen off the agenda - especially when there is a yacht club involved…

Revitalization Unlimited hosted a happy hour where I met operators deeply aligned on tokenizing real estate and packaging alternative investments into accessible vehicles.

This is where I road-tested some of what we’re building at Colton Alexander Advisers. The reception was telling. When you frame Puerto Rico plus tokenization plus alternatives as a single integrated offering, people lean in, and they lean in because it solves real problems rather than because it sounds exotic. Access, tax efficiency, and operational simplicity in one structure.

That’s the test I apply to any idea. Does it survive a conversation with a skeptical practitioner holding a drink? This one did, repeatedly.

The Lone Crypto Panel, and the Down-Only Problem

Credit where due. James McConaghy of Eaglebrook and Michael Kosoff of Mariner ran the only dedicated digital asset session at the entire conference, and they did it well.

The framing was right: crypto is no longer a fringe conversation. The real question is how RIAs capture held-away assets, implement tax-loss harvesting, and position for the next generation of wealth.

But the room told its own story. Sparse digital asset presence, and audience questions fixated on price.

Then there was the CoinShares booth, one of the only digital asset firms exhibiting. Their diversified alt-asset ETF, holding a basket of staked altcoin products like Solana, Cardano, Cosmos, and Toncoin, is down roughly 70% at NAV since its October 2025 inception. Net assets sit just over a million dollars, and the correlation to Bitcoin is 0.96.

The real kick in the teeth…is that they charge almost 1% as a fee. 🙄

Think about what that means.

You get full Bitcoin correlation with dramatically worse drawdowns and no diversification benefit. So the question every advisor in that hall was implicitly asking: how is an RIA supposed to allocate client capital to products that have been down-only? Under a fiduciary standard, they really can’t, and until the industry builds products that solve for fiduciary reality instead of crypto-native enthusiasm, that capital stays on the sidelines.

This is the altcoin problem in one exhibit booth. It’s also why my framework has always separated Bitcoin from everything else. Bitcoin is a store-of-value asset class while altcoins are speculative tech bets, and funds that blend the two into a basket inherit the volatility of both and the credibility of neither.

The Hougan Takeaway

Matt Hougan put words to what I felt all week. He’s had an incredible number of conversations with advisors, and they’re genuinely interested in digital assets, just not in coins.

The interest is in stablecoins and tokenization.

The future of wealth management won’t be built on “crypto” as advisors understood it in 2021. It will be built on stablecoin yield and tokenized assets, especially in private markets and alternatives. The same private markets that dominated every stage at EDGE. The rails are blockchain, but the product is access, yield, and efficiency. Nobody in Boca Raton was speculating on dog coins, yet plenty of people were asking how to tokenize a real estate fund.

This is the convergence I’ve been writing about for years. Traditional finance doesn’t adopt crypto. It absorbs the useful parts and discards the rest, and tokenization is the useful part.

The Bottom Line

EDGE was a great event with a great team behind it, and I’ll be back in the fall. But the signal was clear. The wealth management industry has moved past the question of whether digital assets matter and is now sorting out which parts matter. Stablecoins, tokenization, and tax-advantaged structures are winning. Speculative altcoin baskets are losing.

Until next time fam!

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Matthew Snider is the founder of Block3 Strategy Group, author of “Warren Buffett in a Web3 World,” and publisher of the BitFinance newsletter. He holds a Series 65 and MBA, and has been an active participant in digital asset markets since 2015. This article is for educational purposes only and should not be considered financial advice. Always consult with a qualified professional before making investment decisions.

It’s live on the web, free, no login, running entirely in a browser. It works, and I’m glad I made it. The tool itself is the least interesting part of this story - but if you want to check it out here, you can.

What’s worth your time is the instinct that produced it.

A year ago, facing the same problem, I’d have bought a prep app and lived with whatever it handed me. This weekend my first move was to build the exact thing I needed. That reflex is new, it’s available to you, and it’s the real story here.

Think about what that changes. The cost of building the exact thing you need has fallen close to zero, and the bottleneck is no longer money or engineers.

It’s whether you notice the problem and reach for the tool. The friction you’ve learned to tolerate, the spreadsheet that eats an hour, the app that does nine of the ten things you need, the report you rebuild by hand every month, used to feel permanent. Most of it isn’t anymore.

The tool is simple enough to describe in a breath. Behind it sit 74 question generators that spin up fresh numbers every time you load one, so you drill methods instead of memorizing answers. There’s a mode where I type the answer and work the math out by hand, a timed quiz at exam pace, and a worked solution on every question. That’s the whole thing.

There’s a deeper reason though that this matters to me.

For the better part of a month I’ve been making a single argument: statutory licensing is the one moat AI can’t commoditize.

Software can’t sit the Series 7 for you or file your U4. Then I spent a weekend using software to build the thing that helps me clear that exam faster. That looks like a contradiction, but it’s the argument in a single frame.

The AI built the ladder. The license is still mine to climb to and hold.

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How it came together

I approached it the way I’d brief a sharp junior analyst who happens to type fast. I didn’t write code by hand. I described outcomes and corrected what came back wrong.

Before building anything, I did the reading. I pulled sample questions and prep PDFs from a range of sources online, and I clipped pages straight out of my Kaplan manual so the model could match the formatting and the way the real questions are worded.

Then I did the thing that seems counterintuitive but is actually the highest leverage piece of advise in this article: I described the outcome I wanted.

• Questions that regenerate with new numbers.

• Answers checked against worked solutions.

• Wrong choices built from the mistakes the exam likes to bait.

• A helpful glossary of terms for me to memorize.

• An Options Matrix reference guide I could use to see various scenarios.👇

The work ran on three tools, each with one job. Think of them as the trifecta that carries an idea from your head to a live link: one to generate the code, one to store it, one to launch it.

• Claude Code is the engineer. It’s Anthropic’s coding tool, and you talk to it in plain English. It writes the code, runs the commands, and fixes what you flag. You never have to open a file unless you want to.

• GitHub is the filing cabinet. It stores the project in one place and tracks every change, so the work isn’t stuck on one machine. I can pick it up from my laptop or my desktop, and Claude Code reads from it to know where things stand.

• Vercel is the launchpad. It turns the code into a live website with a public address, automatically, every time the project updates. There’s no server to manage and no domain to buy. My trainer lives at series7math.vercel.app, an address Vercel gave me for free.

The move that ties them together is a fairly simple workflow once you recognize how the tools .

I tell Claude Code what I want, and I let it drive all three: write the code, save it to GitHub, push it live on Vercel, and handle the logins and wiring in between. I describe, it builds and ships. That’s how an idea becomes a link I can open on my phone, with no part of the chain requiring me to write or read code.

From there I worked in small loops. Claude Code would build a piece, I’d open it, try it, and tell it what was off. The breakeven on a put was subtracting in the wrong direction. The dollar conversion forgot the hundred-share multiplier. Fix that, show me again. Most of the weekend ran on that rhythm. Look at the thing, react to the thing, send it back.

The loop is the whole skill, and it’s more forgiving than it sounds. Nothing I tried first survived intact. The first timed quiz scored wrong. An early generator produced breakevens that were off by the premium. None of that cost me anything beyond the minute it took to say so. When making a change is nearly free, you stop defending weak versions and start replacing them, and the thing gets sharper with every pass.

What made it work came down to one thing: I know the material.

It’s critical that you have some kind of domain expertise with what you are trying to create so you validate the output as helpful and useable, while being able to determine if that output is garbáge (so fancy).

When the model put a formula in slightly wrong, I caught it, because I’ve read the manual and worked these problems by hand. The model brought the typing. I brought the judgment about what good looks like, and that was the part that couldn’t be handed off.

AI doesn’t replace judgment. Full stop.

It replaces the tedious work sitting underneath it. Writing the code to randomize a strike price is tedious. Knowing that a covered call’s maximum loss is the stock cost minus the premium received, and noticing when the screen says otherwise, is judgment.

How you can win doing this too

You don’t need to code, and you don’t need a technical background. You need a problem you understand, the three tools above, and the willingness to run the loop. Here’s the path I’d hand to anyone starting out.

1. Pick a real problem you already have. Start with the friction you tolerate every week, not a moonshot. Small and annoying beats big and vague.

2. Gather the raw material first. Know the subject well enough to tell right from wrong. That domain knowledge is what separates a version that works from one that only looks like it does.

3. Describe the outcome, not the code. Say what ‘done’ looks like and let the tool work out how to get there.

4. Work in short loops. Build a piece, test it, say what’s wrong, repeat. You’re steering, not typing.

5. Be the judge. The machine is fast, confident, and sometimes wrong. Your standard for what’s right is the part that can’t be outsourced.

This part should sit with you whether or not you ever touch the Series 7. We’re early in an agentic economy, and the edge is shifting from people who can do the work to people who can direct the tools doing it.

From a business angle, someone in your market is already compounding small builds while their competitors wait for a budget line. From a personal angle, this is the cheapest leverage available, and it’s sitting in a browser tab you already have open. The skill getting scarce is knowing what’s worth building and telling when the result is right.

The typing in the middle keeps getting cheaper by the month.

I’ll be living in this trainer for the next six to eight weeks, drilling toward the SIE and then the Series 7. It’s free, it’ll stay free, and the link’s below. What I’d want you to take from it isn’t the trainer but the habit behind it. Build the next thing you wish existed, then the one after that. The muscle is what compounds.

Until next time - keep building friends!

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Matthew Snider is the founder of Block3 Strategy Group, author of “Warren Buffett in a Web3 World,” and publisher of the BitFinance newsletter. He holds a Series 65 and MBA, and has been an active participant in digital asset markets since 2015. This article is for educational purposes only and should not be considered financial advice. Always consult with a qualified professional before making investment decisions.

We had the broad idea. Build a research engine that could take rough trading ideas, test them against real market data, keep track of what worked, kill what didn’t, and eventually help us turn the best ideas into things people can actually use: research notes, dashboards, and maybe, one day, live trading systems.

That sounds clean when you write it in a single sentence.
In practice it’s messy. Very messy.

Trading research is full of traps.

• A strategy can look great because it accidentally peeked into the future.

• A backtest can look amazing because it worked during one stretch of history.

• A set of settings can look “optimized” when really it was fit too tightly to noise.

• A chart can look convincing while the data underneath is doing something dumb.

The goal was never simply to have an AI go find trades. That’s too easy to say and far too dangerous to trust.

The goal is to build something closer to a research factory, disciplined enough to take an idea, ask the right questions, test it in layers, keep the evidence, and make it easier for a human to decide whether it deserves any more attention.

This week, that factory started to feel real.

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Three parts that have to click

The engine only works when three things move together:

1. human intuition,

2. AI-assisted research, and

3. A dashboard that keeps score.

Take any one of them away and you’re back to guessing.

The human part still matters most. We can talk through an idea in plain English. It might start as something simple, like “what if a certain market pattern works better after a strong move?” Or “what if this setup behaves differently in futures than it does in stocks?” Or even “this looks interesting, but I don’t know how to define it yet.”

That’s where the conversation with Skyla (our Hermes-based AI agent leveraging Codex) has become useful. Instead of needing to turn every passing thought into a fully specified research plan, we can message Skyla back and forth and she helps translate a vague hunch into something more structured: what market, what signal, what rules, what should count as success, what would prove the idea wrong, and what follow-up tests would make sense if the first pass looks promising.

What’s more fun, we can leverage Skyla to help prove, debunk or improve upon ideas that are out there in the wild and on twitter. Take this conversation as an example where I dropped an interesting idea that I found and asked her to evaluate it…

The fact is, most trading ideas should die quickly, and that isn’t a failure of the process but the entire point of it.

A good research process protects you from falling in love with a chart. It makes testing cheap, and it makes it easy to say “nope, this probably isn’t real.” When something does survive the first round, though, the system finally has a place to put it.

Mission Control

That place is Mission Control, our internal dashboard, and it’s one of the bigger pieces we improved this week.

Mission Control is becoming the cockpit for the research engine. It’s where ideas, test runs, results, and the evidence behind them start to show up in a form a human can actually inspect, rather than being buried in logs, scattered across random files, or dependent on somebody remembering what happened two days ago.

The screenshot above is a small example, but a meaningful one. It shows one trial we kept from an early research path. You can see which market it traded, how many long and short positions it took, and the numbers that actually matter: how much it made, how deep the worst losing stretch ran, how many trades it took, and whether the returns justified the risk. There’s also room for the charts that show the account climbing and the ones that show it bleeding.

This isn’t us saying we found the magic trade, so please don’t read it that way. What it shows is more important than any single result. The machine can now run a trial, keep the result, and present the evidence in a format a human can review. That’s the difference between playing with ideas and building a real research process.

Building the questions into the machine

One of the biggest challenges with AI-assisted trading work is trust. If an AI tells you “this strategy looks good,” that’s basically useless on its own.

• Good according to what?

• Tested where?

• Over what period?

• How many trades?

• What happened when it was losing money?

• Did it cheat?

• Did it try so many variations that one was bound to look good by accident?

We’re trying to build the system so those questions aren’t optional, but baked into the workflow. The engine breaks research into stages. A rough idea first becomes a clear, testable setup, then passes basic sanity checks, then produces trial evidence, then faces tougher evaluation that helps separate real signal from lucky noise. If it fails, it gets killed cleanly.

If it survives, it carries its evidence forward.

That’s the part I’m most excited about. Not because any single test result is exciting on its own, but because the process is starting to compound.

We also made progress on the autoresearch side, which lets the system move from one research step to the next without us babysitting every action. It can take a structured idea, run a bounded test, record what happened, and tee up the next decision. Bounded is the important word. We’re not building a runaway black box that fires off endless experiments and declares victory, so the system carries guardrails: limits on how many loops it can run, rules for when to stop, thresholds for what gets promoted or killed, and human approval wherever the work could have real consequences.

Here’s a sample of some trial runs our autoresearch agents were able to curate and display within Mission Control for review.

Finance doesn’t reward people for moving fast and breaking things.
It rewards people for being a little less wrong, over and over again.

Buffett Framework: “Risk comes from not knowing what you’re doing.”

The question that drives this whole build isn’t whether the engine can surface something that looks good, but whether we can tell a real edge from a lucky one before a single dollar is ever at stake.

Answers people can actually read

A research engine is only useful if people can understand what it found. If every result means digging through raw data or reading dense technical output, it’ll never become part of a real decision.

So we’ve been building toward a cleaner path.

• A human has an idea.

• Skyla helps shape it into a real research question.

• The system runs the first pass.

• Mission Control shows what happened.

• The idea then dies, gets revised, or earns another round.

Eventually, if the evidence is strong enough, that work can become something more polished: a post, a chart pack, an indicator concept, or a strategy note a reader can actually follow.

The Art of the Possible

That’s the long game, and we’re not there yet. We’re still building the engine. The dashboard is improving but isn’t finished. The autoresearch loop works in an early form, though it still needs more wiring, more testing, more operator controls, and more real-world reps. We’re still learning what the system should automate and where a human should stay firmly in the loop.

The progress this week was real, though.

The system is no longer just a clever chat window bolted to a workstation. It’s starting to become an operating layer for research, one that can turn loose ideas into testable ones, run early trials, keep the evidence, and show results in a dashboard instead of leaving them in memory, vibes, or a folder full of screenshots. That might sound unglamorous, but it’s exactly the kind of plumbing serious research needs.

The fun part is imagining where this goes and thinking through the art of the possible.

As we keep building, we should be able to ask better questions faster, compare new ideas against old ones, and watch which families of strategies survive while others die, building a library of tested patterns instead of a graveyard of half-remembered experiments.

For readers, that means the research we share over time should get better too. More evidence behind the claims, cleaner explanations, and more transparency about what failed. More confidence that when we say something looks interesting, it’s been through more than a pretty chart and a good story.

That’s the part I keep coming back to. The engine isn’t meant to replace judgment, but to make it sharper. This week, we got a little closer.

Onward and upward fam! 📈

🛑 SIGN UP HERE BELOW TO BE PART OF WHAT WE’RE BUILDING! 🛑

I’m building the early cohort for when the Discord opens and the first indicators ship. If you want a seat, this is where to claim one.

Interested? Fill out the 30-second interest form here. 👈

This Week In 2 Mins

I Found a Way to Invest in the Robot Boom on the Nasdaq (June 2)

A reader flagged a new Nasdaq ticker, $BOT, and it turned out to be the first closed-end fund built to give regular investors a single-ticker stake in private humanoid robotics names like Figure AI and Apptronik.

It runs the same premium-to-NAV engine MicroStrategy used for Bitcoin, which is both what makes it interesting and where the risk hides. The catch is that its NAV is a quarterly estimate of private companies, so the price can drift far from any value you can actually verify, and the loop that funds the buying can run in reverse just as easily as forward.

I’m not a buyer here yet, but I built a monitor to track the premium or discount, because that gap, not the robots, is the real story.

Read the full article here.

Saylor Finally Sold. Here’s the Part Nobody’s Pricing In. (June 4)

Bitcoin for the first time in four years this week, though it was only 32 coins, about $2.5 million, to cover a payment it had promised investors.

The number itself is noise, but what it hinted at isn't: the product the company uses to raise money slipped below the $100 level it needs to keep issuing, its cash cushion is down to roughly six months against about $1.7 billion a year in promised payments, and Bitcoin now trades below the company's average cost. None of that forces anything today, yet for the first time we watched the machine run in reverse instead of forward.

The point I keep shouting is that Saylor isn't Bitcoin and Bitcoin doesn't need Saylor, so the real risk worth watching is that its biggest holder turns out to be its most fragile one.

Read the full article here.

This Week’s Winners…🏆

• Marvell (MRVL). Nvidia's Jensen Huang called it the next trillion-dollar company on Tuesday, and the stock soared more than 25% in a session to a fresh all-time high, helped by a $2 billion Nvidia investment and a spot in the S&P 500 starting June 22. It gave some back in Friday's chip rout, but it was still the week's headline name, now up more than 130% on the year.

• The US labor market. May payrolls came in at 172,000 against expectations of around 88,000, with unemployment holding at 4.3%. A genuinely strong report, even though Wall Street treated it like bad news (more on that below).

And Losers 📉

• Bitcoin and the broader crypto market. Bitcoin slipped under $62,000, roughly 51% below its October high near $126,200, with about $1.5 billion in leveraged longs wiped out and a record streak of spot Bitcoin ETF outflows. Saylor's 32-coin sale didn't start the slide, but it didn't help the mood either. Here’s the one week look…

  

• Chip stocks and the AI trade. The group that led the rally led the retreat. Friday's selloff knocked the Nasdaq down 4.18% to 25,709.43, its biggest drop since April 2025, with Nvidia off 6% and the chipmaker gauge down 10%. Broadcom fell about 14% after earnings despite revenue topping $22 billion. The S&P dropped 2.64% and the Dow lost 695 points, and the S&P's run of weekly gains snapped at nine, so close to everyone had a rough Friday.

• Anyone hoping for a rate cut. That strong jobs report pushed traders to start pricing in a Fed rate hike this year rather than a cut, and Treasury yields jumped with them.

  ---

What’s On Deck the Week of June 8th

• May CPI, Wednesday June 10 at 8:30am ET. The inflation print everyone’s waiting on, made louder by Friday’s hot jobs number. PPI follows Thursday the 11th, and both land with the June 17 Fed meeting one week out, which makes them matter more than usual.

• SpaceX IPO, reportedly around June 12. Reports saying the company is targeting $75 billion raised at $135 per share. Investor demand reportedly is already about 2x oversubscribed, with roughly $150 billion of demand against the planned raise, though allocations can still change. It will be the largest IPO in history.

• I’ll be at Wealth Management EDGE in Boca Raton, June 9 to 11. If you’ll be there, or anywhere in South Florida that week, reply and let me know. Would love to connect in person.

Matthew Snider is the founder of Block3 Strategy Group, author of “Warren Buffett in a Web3 World,” and publisher of the BitFinance newsletter. He holds a Series 65 and MBA, and has been an active participant in digital asset markets since 2015. This article is for educational purposes only and should not be considered financial advice. Always consult with a qualified professional before making investment decisions.

Just 32 coins, about $2.5 million, sold to make a payment it had promised investors.

Around the same time, a product the company built to always be worth $100 quietly slipped to about $95, and Bitcoin itself kept sliding, down below $64,000. None of those numbers is big. Put them together, though, and they’re worth talking through, because the story underneath is simpler than the headlines make it sound.

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What actually happened

A while back, Strategy started selling an interesting product that was relatively new to the crypto world. Think of it like a high-yield savings certificate.

You hand over $100, and the company promises to pay you $11.50 a year, forever, in cash. That’s it.

People liked it, the company raised billions, and it turned that money into Bitcoin. One rule makes the whole thing work: that certificate has to keep trading at around $100.

While it does, Strategy can keep selling fresh batches and keep buying Bitcoin. The moment it slips below $100, selling more becomes like offering $100 gift cards for $95, where you lose a little on every one.

For most of a year, that certificate sat right at $100.
This week it didn’t.

It hasn’t climbed back to $100 since May 14, and it kept sliding, closing near $94 on June 3. As I write this, almost none of it is changing hands above $100, which is the level Strategy needs in order to sell fresh batches. The engine it uses to raise money and buy Bitcoin has, for now, switched off.

Now the part that matters more than the price.

Those promised payments add up to about $1.7 billion a year. The 32 coins Strategy sold covered maybe half a month of that. Meanwhile the company’s cash, the rainy-day account it draws on to make those payments, sits at around $900 million, roughly six months’ worth. A year ago that cushion was measured in years. Today it’s measured in months per CoinDesk.

One more thing has happened since the sale.

Bitcoin has kept falling, down toward $63,000 as I write this, which is below the roughly $75,700 the company paid on average. Their entire pile is now worth less than they paid for it, at least on paper. That doesn’t force anything on its own, but it’s the backdrop against which every one of those monthly payments still has to be made.

Why 32 coins spooked everyone

The coins themselves are nothing. Saylor said outright he’d probably sell a little to make a payment, just to prove he could, and he still buys far more than he sells. The worry isn’t the size, but what it hinted at.

One analyst put it well back in January: Saylor can buy twenty thousand coins in a week and nobody blinks, but the day he sells even a couple hundred, the market panics.

This week was a small taste of exactly that. Another analyst this week called it the first real crack in the structure.

The treadmill nobody mentions

Here is the heart of it, and it’s something I wish more of us thought about before buying anything built on top of Bitcoin.

Bitcoin doesn’t pay you anything to hold it. It’s like a gold bar or a great painting, it just sits there and, we hope, becomes worth more.

That’s fine if you bought it with your own money and you can wait. It becomes a problem if you’ve promised someone $1.7 billion a year in cash, because a gold bar doesn’t write checks. You either keep bringing in new money, or you start selling the bar.

Saylor admitted as much. By his own math, Bitcoin has to climb about 2.3% every year just to cover those payments without selling stock. Picture a treadmill set to a slight incline. You have to keep walking just to stay in place. If Bitcoin runs hot, that’s easy. If it stalls or drops, the belt keeps moving under your feet.

BUFFETT FRAMEWORK QUESTION: Would you buy the whole thing?

Forget the share price and ask whether you’d want to own the entire company. You’d own a pile of Bitcoin that pays you nothing, plus a stack of promises to hand out about $1.7 billion in cash every year, backed by a bank account with maybe six months in it. It only works if the Bitcoin keeps climbing faster than the promises pile up.

Buffett built Berkshire on the opposite setup, where the money came in first and the assets paid their own way. It’s worth knowing which of those two you’re actually holding.

The same machine can spin backward

For years this was a beautiful machine, and I don’t say that to knock it. People trusted it so much they’d pay more for a share of Strategy than the Bitcoin inside was even worth. The company used that goodwill to sell more, buy more Bitcoin, and pack a little more Bitcoin behind every share, which made people trust it even more. Round and round, up and up.

The trouble is that the same wheel can spin backward.

Once people stop paying extra, and once that $100 certificate slips below $100, selling more stops being clever and starts losing money. The payments, though, don’t stop. They come every month no matter what. When the easy money dries up, the only thing left to sell is the Bitcoin itself. That’s what this week showed, in miniature.

Those 32 coins went to making a payment rather than buying more. There’s a competitor now too, Strive, paying 13% on a similar product that’s holding its value better, which makes Strategy’s 11.5% look thin right when it can least afford to sweeten the deal.

The Key Takeaway

Here is what I most want you to walk away with.

Saylor is not Bitcoin, and Bitcoin does not need Saylor. Full stop.

Bitcoin ran fine for eleven years before this company bought a single coin, and more people own it today, through funds, countries, exchanges, and regular folks, than ever before.

Strategy holds about 4% of all the Bitcoin there will ever be. That’s big enough to push the price around, and small enough that Bitcoin wouldn’t miss a beat if the company vanished tomorrow. What Saylor did was bring a flood of money and attention, and he also changed the story, turning Bitcoin from quiet, neutral money into the engine room of one company’s financial machine.

Some longtime holders love him for the bridge he built, while others feel he’s bent their asset to serve his balance sheet. Both can be true. The catch is that when adoption rides on one big, heavily borrowed-against player, it carries a way to fail that simply holding Bitcoin yourself does not.

Where I could be wrong, and whether it’s over

Now the fair side, because I won’t sell you a panic.

Six months of cash isn’t zero. The company has bought far more than it’s sold for years, even if it’s paused new buying since the middle of May, and that certificate has bounced back toward $100 before, usually around its payment dates. Plenty of smart people looked at this week and shrugged, and on the narrow facts they have a point.

What I’m describing is a bad-case story, not a prediction, and it needs three things to line up at once: Bitcoin flat or falling, the certificate stuck below $100, and that cash cushion running thin. What changed this week isn’t the odds, but that we finally watched the machine run in reverse with our own eyes.

So, is it really over? No, not this, and not now. A small sale to make a payment is not the death of Bitcoin, and anyone shouting that it is, is mostly selling you their own fear. The smarter move is to know what to keep an eye on.

• That $100 certificate. If it keeps trading below $100, that’s the clearest warning light. There’s even a holder vote on June 8 about paying those dividends more often, a sign of how much keeping that level matters.

• The company’s cash. Six months is the number that turns a worry into a real problem if it keeps shrinking.

• How often, and how much, they sell. One payment’s worth of Bitcoin is noise. A habit is not.

• The competition. Paying 11.5% while a rival pays 13% is a standoff that can’t last.

None of those is flashing red today, though a couple are amber. The company and the coin were never the same thing, even with 4% of all Bitcoin sitting on one balance sheet, and Bitcoin’s strength was never going to come from a single buyer.

The real risk worth watching is that its biggest holder turns out to be its most fragile one. Watch it with clear eyes, not fear, and don’t let anyone tell you those 32 coins were the whole story. They were the preview.

Until next time - trade safely fam!

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Matthew Snider is the founder of Block3 Strategy Group, author of “Warren Buffett in a Web3 World,” and publisher of the BitFinance newsletter. He holds a Series 65 and MBA, and has been an active participant in digital asset markets since 2015. This article is for educational purposes only and should not be considered financial advice. Always consult with a qualified professional before making investment decisions.

A reader sent me a ticker this week with a simple question. What is this, and should I be watching it? The ticker was $BOT, and the further I dug, the more it became the kind of thing I enjoy taking apart here. The robots make the headline. The wrapper they sit inside is the real story, and it borrows its design straight from a playbook that crypto investors already know well.

Let me walk you through what it is, why I think it is worth watching, where the opportunity sits, and the part I would slow down on before doing anything.

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What RoboStrategy Really Is

RoboStrategy, Inc. began trading on the Nasdaq under the ticker $BOT on May 11, 2026. Its stock had never traded publicly before that day, so this is a genuinely new instrument rather than a rebrand of something older.

The company is a closed-end management investment company.

In plain terms, it is a fund with a fixed share count that trades like a stock. What makes it unusual is the mandate.

RoboStrategy is the first public closed-end fund built specifically to give ordinary investors exposure to a portfolio of private, pre-IPO, and public robotics and physical-AI companies.

The kind of access that has historically been gated behind venture capital now sits behind a ticker you can buy in a brokerage account.

The portfolio is concentrated and recognizable. It includes Figure AI, Apptronik, Dyna Robotics, Standard Bots, Dexmate, and Path Robotics, with reported average check sizes around $7 million dollars per round. Figure and Apptronik dominate by disclosed value, and most of the rest carry private marks that have not been made public.

The fund is run by Andrew Kang, a former crypto investor who co-founded Mechanism Capital and has backed Figure directly. It launched with a $200 million dollar equity commitment and up to $2 billion dollars in committed financing. The capital is permanent, which means the fund is not forced to return money on a venture timeline and can hold its positions for as long as it wants.

That permanent-capital structure is the tell. RoboStrategy describes itself as inspired by the model that Strategy, formerly MicroStrategy, used to hold bitcoin. Once you see that lineage, the whole thing reads differently.

Why I think it’s Worth Watching

Three things make this listing interesting, and the robots are the least of them.

1. Access. Most of the marquee humanoid companies are staying private far longer than the last generation of tech startups did. Figure has raised close to $2 billion dollars and carries a $39 billion dollar mark without being anywhere near a public listing. Apptronik tripled its valuation to roughly $5.5 billion in a single funding extension this February. For a public-market investor, there has been no clean way to participate in that value creation while it happens, and this is the first vehicle structured to change that.

2. Timing. Robotics funding hit a record in 2025, with startups raising close to fourteen billion dollars against roughly $8 billion the year before. Capital is flowing into the sector faster than public vehicles can absorb it, which creates demand for exactly this kind of wrapper. Whether that demand is healthy or frothy is a separate question, but it is real.

3. The epistemics. This is the reason I care most. RoboStrategy is a clean live experiment in a structure that has already confused the market once. The question of what the price actually measures, and how far it can drift from the value underneath it, is the same question I ask about every backtest and every Sharpe ratio. The mechanics here just make the gap easier to see.

The opportunity, and the MicroStrategy Parallel

To understand the opportunity you have to understand the loop, and to understand the loop you have to start with Strategy.

Strategy is a software company that turned itself into a bitcoin holding vehicle.

It issues equity and convertible debt, uses the proceeds to buy bitcoin, and has frequently traded at a large premium to the value of the bitcoin it holds. That premium is the engine. When the stock trades above the value of its assets, the company issues new shares at that elevated price, raises more cash than the value of the ownership it gives up, and buys still more bitcoin. Existing holders end up with more bitcoin per share than they started with, which helps justify the premium that started the cycle.

RoboStrategy is porting that engine to robotics.

When it works, the loop is powerful.

A premium funds the buying, and the buying defends the premium. A holder gets concentrated, single-ticker exposure to a basket of private robotics companies, plus optionality on the cycle compounding in their favor. If Figure or Apptronik eventually goes public at a higher mark, the fund’s stake gets revalued upward, and the holder captured that move without ever needing access to a private round.

There is also a quieter source of return that has nothing to do with the robots. The premium or discount itself moves, sometimes sharply, so a patient buyer who acquires shares at a discount to a conservative estimate of value carries a very different risk profile than someone buying into a rich premium. The structure creates its own tradeable variable on top of the underlying.

How to Think About Risks

Here is where the same structure that creates the opportunity creates the danger, and where I would slow down. Start with what a price actually tells you in this fund.

A closed-end fund has two numbers that rarely match:

1. the market price, which trades live every second, and

2. the net asset value, which is the fund’s own estimate of what holdings are worth.

For a fund holding liquid assets, NAV is easy to calculate and the two numbers stay close. For a fund holding mostly private, pre-IPO companies, NAV is a quarterly model estimate based on the last round each company raised. The price moves daily. The value it is supposedly tracking updates on a lag, and even when it updates, it is an estimate rather than a market-clearing price.

So the straight answer to what is really going on with the price is that the fundamental value is opaque by construction. You are not buying a number you can verify. You are buying a model output wrapped in market sentiment, and the sentiment can dominate the model for long stretches.

Buffett Framework
“Price is what you pay. Value is what you get.”

With a closed-end fund holding private companies, the price trades live and the value is a quarterly estimate, so the two can drift further apart than usual. The discipline is to watch the gap, not just the price.

Layer the risks and the picture gets clearer.

• Sector risk sits at the bottom. Robotics and physical AI are cyclical, capex-linked, and sentiment-driven, and a buyer carries all of that thematic beta.

• Idiosyncratic private-name risk sits in the middle. The portfolio is concentrated in a handful of pre-IPO companies, so a single down-round or a stalled financing flows straight into NAV. Figure shows the fragility well. Its $39 billion dollar mark sits on revenue estimated in the low tens of millions, and when BMW announced a humanoid pilot at its Leipzig plant this February, it chose a competitor’s robot rather than Figure’s. None of that shows up in a quarterly NAV until the next mark, if it shows up at all.

• Premium or discount risk sits on top, and it is the one most likely to surprise people. The reflexive loop runs in reverse just as easily as it runs forward. A discount can become self-reinforcing, where a falling price makes new issuance dilutive instead of accretive, which removes the engine that was defending the price. A fund only weeks into public trading has almost no history to tell you how its premium behaves under stress, and the early life of these vehicles is exactly when the premium is least anchored.

So the framework I would use is simple to state and harder to practice. Treat NAV as a model output rather than a price. Watch the premium or discount as the primary variable, not the share price in isolation. Pay attention to share issuance, because the pace of issuance tells you whether the loop is running forward or backward. Size any position to the understanding that the top risk layer can swamp the bottom two for months at a time. I am not telling you to buy it or to avoid it. I am telling you that if you do buy it, the premium to NAV is the thing to watch above the robots.

How BOT, MSTR, and a Robotics ETF Compare

The table makes the point cleanly. BOTZ tracks its holdings tightly because they are liquid and priced all day. MSTR can detach from its NAV, but at least that NAV is a live bitcoin price. RoboStrategy can detach from a NAV that is itself an estimate, which stacks one layer of uncertainty on top of another.

What I’m Watching 👀

Should you buy $BOT, probably not right now. It’s extremely volatile as a very new and illiquid security. I’m certainly not a buyer right now…but I am an active watcher.

I built a small monitor for this one with Claude Code, because it’s a good test case and the data is useful whether or not anyone trades it. The monitor watches the premium or discount to the last reported NAV, the fund’s share issuance activity, the funding news for the underlying private names, and the divergence between BOT and a liquid public robotics basket. The divergence between the two is close to a pure read on sentiment, since the public basket strips out most of the shared sector beta. I will report what it surfaces in future issues.

The broader lesson travels well beyond one ticker. A number that looks precise can still be measuring something soft underneath, and the discipline is in asking what the number actually represents before you act on it. That is true of a NAV on a closed-end fund, and it is true of a Sharpe ratio on a backtest.

Until next time - trade safely fam!

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Matthew Snider is the founder of Block3 Strategy Group, author of “Warren Buffett in a Web3 World,” and publisher of the BitFinance newsletter. He holds a Series 65 and MBA, and has been an active participant in digital asset markets since 2015. This article is for educational purposes only and should not be considered financial advice. Always consult with a qualified professional before making investment decisions.

Sources

• RoboStrategy, Inc. Nasdaq listing announcement, GlobeNewswire / Nasdaq, May 11, 2026

• RoboStrategy SEC Form 497AD, FY2026

• Reporting on the $200M / $2B commitment and Andrew Kang background (Mechanism Capital)

• Figure AI Series C announcement, The Robot Report, September 2025 ($39B post-money)

• Figure AI funding and BMW Leipzig pilot context, TechMarketBriefs, April 2026

• Apptronik Series A extension coverage, CNBC and Bloomberg, February 2026 (~$5.5B)

• Robotics sector funding totals, Crunchbase News, February 2026

• Show the real numbers.

• Show the strategies that died.

• Let the track record stand somewhere anyone can check it.

That’s the whole thesis, and it’s why I’m careful about what I put my name on.

So when I tell you I’ve joined Duon Labs as a formal advisor, I want to be straight about the why. The deck didn’t win me over, but the work did. Their team is building in the open and - more importantly - shipping.

Let me give you the plain version of what that is.

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A foundation model, pointed at markets

You already know what a foundation model is, even if you’ve never used the term. It’s the engine underneath tools like ChatGPT or Claude, one big system trained to understand language that then powers a hundred different apps on top.

Duon Labs is building one of those for financial markets instead of language.

Picture a machine that runs millions of simulated futures every day, thousands of versions of what markets might do next, then writes down where all those futures tend to agree. That shared read becomes a forecast.

• The forecast becomes a strategy.

• The strategy deploys real capital.

• The whole chain, from raw data to live trades, runs under one roof.

Here’s the part that I think is easy to miss:

Most trading bots follow rules a person wrote by hand. Duon Labs’s system writes and tests its own. New versions of the models turn over constantly, each one measured against the last, the better ones kept and the weaker ones retired.

The research loop improves on its own and creates a valuable flywheel effect.

That changes the shape of the business. A traditional asset manager grows by hiring more people. Duon Labs grows by adding compute and letting the loop compound. Think of a wind tunnel for strategies: thousands of designs tested against simulated conditions before a single dollar goes near the real thing.

There’s a quieter advantage in here too.

The engine doesn’t care what it’s pointed at. The same stack that models crypto can model commodities, equities, rates, or anything else with a price history, because it learns from the structure of markets rather than the quirks of one of them. Build the wind tunnel once and you can test aircraft, race cars, and rockets in it. That’s why a commodities sleeve is on the way and why the long-term story isn’t a crypto fund but a research engine that travels across asset classes.

Why the on-chain part matters

Now the piece I care about most.

Every trade Duon Labs makes settles on a public blockchain. That sounds technical, but the consequence is simple. The track record stops being a quarterly letter you take on faith and becomes a ledger anyone can open and check in real time.

Sit with that for a second, because it inverts something critically important.

In most of finance, transparency is an actual cost. You disclose details because you have to by a regulated mandate - not because it helps the business.

With Duon Labs, transparency is the product.

The same property that lets an outside investor audit the strategy also lets a custodian’s risk team underwrite it, lets an advisor report it to clients, and lets a board see exactly what it owns. One feature, doing work across the whole stack.

For a newsletter built on the idea that numbers you can check beat marketing, that’s the entire appeal.

The train has left the station (choo! choo!)

None of this is theoretical, so it’s worth grounding in what the team is shipping.

• Consumer reach most research shops never get near. Duon Labs’s signals sit inside a widget on CoinStats, a portfolio app with a large retail following, and that placement has pulled in more than 3 million monthly widget views. The same intelligence behind the institutional strategies is already living on people’s phones.

• Running on serious on-chain infrastructure. The vaults trade live on Hyperliquid, one of the busiest venues in on-chain markets, and a newer vault launched on MegaETH this spring. Two different network designs, one underlying brain.

• Developers lining up to build on it. Next to the vaults, Duon Labs is opening an API so coders and quant teams can build on the same engine. Almost 200 of them are on the waitlist before it’s even fully open.

Ultimately there are really two stories here:

• One is capital the system runs on its own.

• The other is an engine other people get to build on top of.

Both are already moving.

The art of the possible

The interesting question isn’t whether the engine works but who it works for. A few of the places this could land:

• Custodians and custodial platforms. A custodian can hold a client’s assets safely but can’t do much to grow them beyond basic staking. Duon Labs plugs in as an actively managed yield option where the capital never leaves custody and every trade is verifiable. That clears the compliance bar that usually kills these products before launch, because the risk team can audit the strategy instead of taking a counterparty’s word for it.

• Tokenization issuers and platforms. The hard part of tokenizing a fund isn’t the wrapper but the thing inside it: a strategy institutions will actually buy. An auditable, on-chain track record is exactly that, a transferable vehicle any allocator can verify before committing a dollar. The issuer distributes through rails it already runs, and the underlying does the convincing.

• RIAs and wealth managers. Most advisors still can’t offer real digital asset exposure they can stand behind, so they default to a spot ETF or to nothing. This is actively managed exposure, held at a qualified custodian, and reportable down to the individual trade. An advisor can pull up the actual position on-chain in front of a client, which turns a hard conversation into a simple one. This one feels like the long-term destination.

• Asset managers and allocators. An allocator’s job is to trust a manager’s numbers between quarterly letters, which is mostly an act of faith. Here the sleeve is verifiable continuously rather than reconciled once a quarter. You stop auditing the past and start watching the present.

• Trading desks and quant shops. A desk doesn’t want someone else’s black box but better inputs for its own. Duon Labs’s read arrives through an API as one more signal that stacks on top of existing models, not a replacement for them. It’s edge a desk can test against its own book before ever leaning on it.

Different customers, one engine underneath. Every dollar of research compounds across all of them, which is what makes the economics hard to copy.

My role, and where it stands

I’m advising on methodology and validation, on how research gets pressure-tested before it touches live money, and on how to frame the work for the institutional investors who might one day allocate to it. I bring a Series 65, prior experience running a digital asset strategy, and a low tolerance for flattering numbers. Coincidentally, we’re complementary because I’m building an engine to auto-curate indicators that could be used by Duon Labs’ to hone their agent accuracy.

None of this is finished, and I won’t pretend otherwise. The out-of-sample research is strong, and it’s auditable. Turning research-grade results into consistent live performance is the hard part, and that translation work is a big reason I said yes. I’d rather you hear that from me than find it on the audit page later.

So go take a look for yourself and see what we’re cooking!

The vaults trade on-chain, the model releases are public, and you can watch the whole thing run live here: live.duonlabs.com

I’ve said for a while that crypto + AI is the most interesting place to be building right now. Duon Labs is the clearest example I’ve found of someone doing it out in the open, with the receipts attached. I’m glad to be along for it, and I’ll keep showing you what I learn, the wins and the misses both.

Excited to keep you posted on the opportunity. If you’re interested in learning more about what their building or their fundraising efforts - please reach out!

🛑 SIGN UP HERE BELOW TO BE PART OF WHAT WE’RE BUILDING! 🛑

I’m building the early cohort for when the Discord opens and the first indicators ship. If you want a seat, this is where to claim one.

Interested? Fill out the 30-second interest form here. 👈

This Week in Two Minutes

Your Software Is About to Start Paying Its Own Bills (May 26)

Keyrock, Coinbase, Tempo, and Virtuals published twelve months of real machine-to-machine payment data.

AI agents settled $73 million across 176 million transactions between May 2025 and May 2026, with 98.6% of that flow moving through USDC. The sustained Q1 2026 run rate was $11 to $15 million weekly.

Why it matters: a USDC transfer on Base costs about 1/100th of a cent, while a Stripe card rail costs about 31 cents. For a $0.31 transaction, one rail leaves the merchant with $0.3099, the other with $0.001. The old rails can’t carry that traffic at that price point. Post office vs. email, fifty years later.

The part worth holding: roughly 74% of agent volume currently flows through Coinbase’s chain, Coinbase’s stablecoin, and Coinbase’s facilitator. That’s the most vertically integrated payment stack since Stripe.

Read the full article here.

Tokenization’s Missing Buyers (May 28)

A few days ago, Adam Blumberg published a piece in the Tokenized Asset Coalition’s Industry Veteran Series that did something the tokenization industry has spent five years avoiding.

He runs an SEC-registered RIA built for the crypto-native UHNW investor, and he still can’t allocate to tokenized RWAs at scale. The buyers aren’t missing, they’re blocked. Five operational barriers (custody fragmentation, opaque token-to-asset data, KYC rebuilt at every issuer, no reporting integration, four different income mechanics) sit between conviction and allocation.

Tokenization works for stablecoins and tokenized Treasuries because the underlying is liquid and the data is clean. It stalls in private credit, real estate, and specialty finance because the operational rails to hold those assets don’t exist yet.

The article ties to the RIA work I’m doing in Puerto Rico, and the gap that work is built around.

Read the full article here.

Winners This Week🏆

• Public-chain tokenization rails. 2 big wins in one week!

  • DTCC announced a partnership to tokenize Russell 1000 equities and US Treasuries on Stellar ($XLM) by 1H 2027. Paxos became the first blockchain-native firm registered with the SEC as a clearing agency and central securities depository, after seven years of regulatory back-and-forth. The legacy infrastructure that has run US securities for decades is migrating to public blockchain rails. If you’ve been waiting for a structural signal that tokenized real-world assets are a real category and not a slide deck, this week was it.

  • I guess the $XLM market liked the news…

  

• US regulated crypto derivatives. Kalshi got the first CFTC approval for a Bitcoin perpetual futures product, with stated plans to expand to more than a dozen currencies. Coinbase received a separate no-action letter allowing perpetual futures through its Bermuda affiliate, with BTC, ETH, and stablecoins as eligible collateral. US-based traders no longer have to use offshore venues to get perp exposure. Better tax treatment, lower counterparty risk, and a competitive landscape that suddenly looks domestic.

• Bank-issued stablecoins. SoFi launched SoFiUSD, a bank-issued dollar stablecoin available inside its app with Ethereum and Solana support. Banks have moved from regulating stablecoins to issuing them. The competitive set against USDT and USDC just changed shape, and the door is now open for other US banks to follow the same playbook.

• Hyperliquid and the DEX thesis. The 11-person team’s HYPE token sits within 4.5% of its all-time high after ICE CEO Jeffrey Sprecher called the protocol “bigger than Nasdaq” at the Bernstein conference and disclosed multiple meetings between ICE and the team. Legacy exchanges have stopped pretending decentralized rivals don’t exist. That’s a meaningful change in posture from the firms that run the regulated markets.

And The Losers…📉

• Long-duration bond holders. The 30-year Treasury yield hit 5.19% earlier this week, the highest since July 2007. The 10-year touched 4.67% before easing to 4.44% Friday on tentative US-Iran ceasefire news. Anyone holding duration through this repricing took a beating, and the bid-to-cover ratios on recent 10- and 30-year auctions show real demand strain at the long end. Yields eased late in the week, but the structural backup is the story.

• Anyone positioned for rate cuts. Fed funds futures now show markets assigning a 46% probability to a rate hike in December, not a cut. Six months ago the consensus was for multiple cuts in 2026. Core PCE came in at 3.3% year-over-year this week, still well above the Fed’s 2% target. The trade that the Fed would ride to the rescue this summer has been mostly squeezed out.

• Small caps. The Russell 2000 trailed every major index again this week, finishing in the red while the S&P, Dow, and Nasdaq all closed green or near it. Smaller balance sheets carry more funding-cost sensitivity, and the rate-hike repricing makes that exposure expensive. The gap between large-cap AI beneficiaries and the rest of the economy keeps widening.

• Bitcoin spot and the “uncorrelated asset” pitch. BTC trading around $73K and underperforming AI and semiconductor stocks while the broader market notches highs. Spot Bitcoin ETFs hit a record nine-day outflow streak with $2.8 billion pulled, the longest run of withdrawals since they listed in January 2024. The narrative that Bitcoin trades independently of risk assets is being tested in real time, and right now it’s struggling to hold.

What’s on Deck This Week: June 1

• June FOMC meeting and the jobs report. Non-farm payrolls land Friday, June 5. With rate-hike expectations creeping back into futures and core PCE at 3.3%, the labor data is the cleanest read on whether the Fed has room to move in either direction this year. The June FOMC follows mid-month, and any pivot language from Chair Warsh moves both equities and fixed income.

• Iran ceasefire verification. The reported 60-day memorandum of understanding between the US and Iran extends the current truce and gradually restores tanker flow through the Strait of Hormuz. The deal is contingent on Trump approval. Oil markets, Treasury yields, and inflation-linked positioning all move with the headline risk on this one.

• ETF flows as a forward indicator. Watch whether the nine-day Bitcoin ETF outflow streak breaks or extends. Flows have led price by a few sessions this cycle. The same read applies to equity ETF flows heading into the FOMC.

• Stablecoin regulatory deadlines. The GENIUS Act implementation deadline is July 18. MiCA’s transitional period ends July 1. Neither contains provisions for autonomous machine-to-machine transactions, which is the gap the agentic commerce piece spent time on. Worth watching how issuers and regulators handle the mismatch.

Until next time! Trade safe out there fam 😎

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Matthew Snider is the founder of Block3 Strategy Group, author of “Warren Buffett in a Web3 World,” and publisher of the BitFinance newsletter. He holds a Series 65 and MBA, and has been an active participant in digital asset markets since 2015. This article is for educational purposes only and should not be considered financial advice. Always consult with a qualified professional before making investment decisions.

It named the problem out loud.

Blumberg runs Protocol Wealth, an SEC-registered RIA built for the crypto-native ultra-high-net-worth investor. He has the clients. He has the conviction. He has six years of teaching this stuff before he ever launched the firm. Despite all of that, he can’t allocate to tokenized real-world assets in any meaningful way.

The reason isn’t skepticism. The piece is the opposite of skeptical, and that’s why I think it warrants consideration.

Somebody on the inside is saying out loud that the architecture being built right now will decide whether the trillion-dollar institutional channel ever shows up.

Here’s the part that landed hardest for me.

Walk into any conference that hgihlights “tokenization” today and you’ll hear the same pitches you heard five years ago:

• Democratize access.

• Bring smaller managers onchain.

• Open up regional real estate, agricultural credit, specialty private credit, energy royalties, the long tail of strategies that traditional distribution couldn’t reach.

That’s it. That’s the only pitch that justifies the cost of building this industry.

What’s actually being shipped is tokenized share classes of the BlackRock USD Institutional Digital Liquidity Fund. Tokenized Apollo private credit. Tokenized Hamilton Lane. Tokenized KKR. Real funds, real institutions, real assets. None of that’s in dispute.

The question is whether tokenizing those funds advances the original case for tokenization at all. The answer is no.

Apollo and BlackRock and KKR were not assets that lacked distribution. An RIA who wanted Apollo private credit already had three different ways to get it. The tokenized version is a UI upgrade dressed up as a paradigm shift.

The original promise was about expanding the universe of managers who could compete for capital. The current path is a premium digital wrapper for the trillion-dollar managers who already had every distribution channel they needed.

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Where tokenization actually works

The bottom line is that tokenization works as a technology and foundation for transmitting value between parties when they would normally be illiquid.

The challenge, is that it’s worked in a narrow part of the market that most retail investors don’t think about as “tokenization” at all.

Let’s look at some examples:

• Stablecoins are tokenized dollars. They work.

• Tokenized Treasuries like BUIDL, OUSG, and BENJI are tokenized T-bills, and they’re growing fast because the underlying is homogeneous, the NAV is calculated by an established fund administrator, and the oracle just publishes a daily number.

The data tying the token to the asset is reliable, the income mechanics are clean enough to live with, and the use case (cash management onchain) is sharp.

That’s the easy case. Liquid underlying, transparent pricing, daily marks, simple income structure. Tokenization on liquid markets is largely a solved problem.

What hasn’t been solved is the case that actually justifies the regulatory complexity, the smart contract risk, and all the capital that’s gone into building this industry. Private credit. Real estate. Specialty finance. Royalty interests. Insurance-linked securities. The asset classes where the underlying economics are interesting precisely because the existing distribution machinery couldn’t reach them efficiently.

In those markets, tokenization runs into a problem that doesn’t show up in the marketing decks:

There’s nobody to buy what you’ve built.

The volume problem

Here’s the thing about tokenizing a private investment vehicle. The token can be perfectly designed. The smart contract can be flawless. The compliance modules can be elegant.

None of that matters if there’s no allocator on the other side ready to write a check.

• In liquid markets, the buyers exist. Anyone with a stablecoin and a wallet can buy a tokenized Treasury. The market makes itself.

• In illiquid markets, the buyers are fiduciaries managing other people’s money.

This means they have rules to follow requiring:

• A qualified custodian that supports the specific token.

• Verified accreditation that doesn’t require re-onboarding the client at every issuer.

• The investment position to show up in their portfolio reporting system alongside everything else they manage.

• A defensible answer to compliance about how income is delivered and how it gets taxed.

Blumberg lays out five operational reasons fiduciaries can’t currently buy tokenized alternative assets at scale.

1. Custody is fragmented across multiple platforms with no single coverage path.

2. Token-to-asset data is opaque exactly where it matters most.

3. KYC is rebuilt at every issuer.

4. Reporting doesn’t integrate with the platforms that actually run the wealth-management industry.

5. Income arrives through 4 different mechanisms with four different tax treatments.

None of those problems is technically intractable. All of them require infrastructure that crosses platform boundaries, and the platforms have been building inside their own walls instead.

And herein lies the rub:
you end up with tokenized regional real estate that nobody can allocate to.

Tokenized specialty private credit with low volume because the natural buyers can’t operationally hold it. The promise of tokenization, the one about reaching the manager you couldn’t reach before, dies at the operational layer.

Why this is on my desk

I’m in the middle of standing up a registered investment adviser in Puerto Rico. Part of the work I’m doing with that team is trying to engage this exact problem.

I don’t want to overclaim what we’re building. The infrastructure questions Blumberg names are coordination problems the whole industry has to solve together, and no single RIA is going to fix federated KYC or qualified custodian coverage on its own.

What I can say is that the gap between what tokenization promised and what it’s delivering is the central question I keep coming back to, and the firm I’m helping build is being designed with that gap in mind from day one.

The reason I’m telling you about this isn’t to pitch the RIA, but to make a point about what to watch for as the tokenization narrative gets louder over the next year.

As we progress, I’m excited to keep y’all apprised of the progress we make. The ultimate goal is to build a platform that can unlock many of the challenges we’re seeing related to volume and attract institutional players to participate.

In short…we’re hoping to build it so others will come.

What to watch

The tokenization headlines are going to keep coming. Larry Fink and Boston Consulting Group see this technology growing to tokenize tens of trillions of dollars worth of assets.

Every traditional asset manager will announce something. Every blockchain conference will have a tokenization track. The numbers being projected for tokenized RWAs by 2030 will keep climbing.

Most of that volume, if it materializes, will be tokenized versions of products that already existed.

• Money market funds

• Treasury products

• Real estate

• Share classes of institutional funds you could already access through a broker.

Useful incrementally for cash management and capital efficiency, but not the structural change in who gets to invest in what.

The structural change starts when the long-tail manager (the regional real estate operator with a track record, the specialty lender with differentiated underwriting, the niche credit shop you’d never have heard of through traditional channels) can actually find fiduciary buyers onchain. That requires operational infrastructure built across platform boundaries instead of deeper into single-platform silos.

It also requires fiduciaries to actually show up to participate, which is the slower part of the answer, and the part I’m spending my time on.

Tokenization is an unfinished experiment rather than a failed one.

The work that’s been done at the standards layer, at the custody layer, at the issuance layer is real and impressive. The work that hasn’t been done is the part that connects all of it into something a fiduciary can use to bring a new asset into a real client portfolio.

That gap is where the actual opportunity lives. It’s also where the next phase of this industry gets decided and I’m pumped to be building in a space like this!

Until next time!

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Matthew Snider is the founder of Block3 Strategy Group, author of “Warren Buffett in a Web3 World,” and publisher of the BitFinance newsletter. He holds a Series 65 and MBA, and has been an active participant in digital asset markets since 2015. This article is for educational purposes only and should not be considered financial advice. Always consult with a qualified professional before making investment decisions.

Payments settled in days because humans needed days. Fees existed because humans paid people to staff the desks, run the wires, and resolve the disputes. The whole system was sized for analog speed and analog volume.

We finally have an alternative, and it didn’t arrive because Wall Street decided to upgrade the plumbing. It arrived because the open architecture of blockchain, with its immutability, transparency, and security, turned out to be the only foundation that could support stablecoin settlement and agentic payments at the scale software is about to demand.

Here’s the math that makes it concrete.

A USDC transfer on Base costs roughly one one-hundredth of a cent.
The same payment on a Stripe card rail costs nearly thirty-one cents in fees.

For a $0.31 transaction, the first rail leaves the merchant with $0.3099. The second leaves the merchant with $0.001.

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What Just Happened

On May 21, the crypto market-making firm Keyrock published “Who Pays the Agent?” in partnership with Coinbase, Tempo, and Virtuals.

They curated, 12 months of actual data stemming from real machine-to-machine payments; not slides from a venture pitch.

The findings should tell you where the puck is going:

• AI agents settled over $73 million across roughly 176 million transactions between May 2025 and May 2026, with 98.6% settling in USDC.

• It’s worth noting that Keyrock themselves flag a caveat here revealing that onchain analysis might suggest a meaningful portion of those transactions reflect artificial or gamified activity, and the headline volume figure may overstate genuine commercial throughput by as much as half….but still, not nothing!

• The more grounded signal is the sustained $11 to $15 million weekly run rate in Q1 2026, with a peak of $15.3 million in late March, coinciding with genuine integrations like Nansen and Alchemy rather than airdrop farming.

The agentic economy stopped being a pitch deck and started being an ecosystem with a measurable, if early, run rate.

Why the Dollar Can’t Carry This

Think about the post office and email.

The postal system works fine for shipping a letter, but it can’t carry a message that costs one ten-thousandth of a stamp to deliver. Email didn’t solve that by reinventing the post office; it built a different network with a different cost structure underneath. Both systems still exist. They serve different problems.

Agentic commerce is the same situation, just 50 years later.

Card networks were engineered around a human shopping at a register. Settlement clears in days. A floor fee exists because the rails are expensive to operate and someone has to pay for the chargeback infrastructure. None of that scales down to a software agent paying a data feed three cents for a real-time market quote.

Erik Reppel, who built x402 at Coinbase, frames it this way:

“Paying with stablecoins is actually the logical equivalent to paying in cash.
If I hand you $10, there’s no person who’s going to take 3% of the $10.”

That’s the deeper point. Blockchains haven’t merely made payments cheaper. They’ve returned payments to their pre-intermediation economics.

When three out of four agent transactions cost more in fees than they’re worth, the existing rails become structurally impossible to use.

The Four Lanes of the New Highway

4 major protocols are emerging to serve this market. The names and functions matter more than the technical implementation.

• Visa extended its existing card rails to provision AI-ready tokenized credentials agents can present at checkout.

• Google released AP2, an authorization layer that lets users delegate spending authority to agents using cryptographic mandates.

• Stripe and Tempo co-authored the Machine Payments Protocol (MPP), a payment-method-agnostic standard handling stablecoins, cards, and Lightning through a single HTTP flow.

• Coinbase built x402, repurposing the long-dormant HTTP 402 status code to enable stablecoin payments between machines. (remember, I talked about them at Consensus)

  

The meaningful frame: these aren’t all competing on the same field; they’re stacking. AP2 handles authorization on top while x402 and MPP handle settlement beneath it.

Actual value moves on blockchain rails below that. Visa runs as a parallel lane for transactions where tokenized cards make more sense than stablecoins. For the longer arc on why x402 specifically matters, my earlier DIEM and VVV thesis walked through how this was already showing up in agent-payment tokens.

Who’s Building Which Lanes

Coinbase and Stripe each span five of the six layers Keyrock maps.

Coinbase covers settlement (Base), wallets (AgentKit), the payment protocol (x402), and governance as a 402 Foundation partner. Stripe mirrors this through Tempo, Privy, Bridge, and MPP. Circle covers four layers. Google and Visa span two and one respectively.

The legacy incumbents are paying real money to claim position.

• Capital One acquired Brex for $5.15 billion specifically for its programmable card infrastructure.

• Mastercard purchased BVNK for $1.8 billion.

• Stripe acquired Bridge for $1.1 billion.

The named deals total more than $8 billion in twelve months. If you’re wondering whether the establishment is fighting or buying in, the M&A number is your answer.

The Size of the Prize (where stuff gets nutty!)

Industry forecasts say this gets big. Like, really big.

• Gartner projects $15 trillion in AI-agent-intermediated B2B purchases by 2028.

• McKinsey estimates $3 to $5 trillion in retail agentic commerce by 2030.

• Juniper Research forecasts $1.5 trillion.

• BCG puts US e-commerce alone at $1.3 trillion.

Sure, it’s absolutely worth treating these with appropriate skepticism. Getting from today’s $600 million annualized run rate to $1.5 trillion in 4 years implies a compound annual growth rate of roughly 350%.

For context, the entire stablecoin market grew at about 100% CAGR over 6 years. The agentic projections require growth 3-5x faster than the most explosive period in stablecoin history.

That doesn’t make them impossible. It makes them aspirational, contingent on infrastructure, trust, and regulation all maturing in parallel. The infrastructure is mostly ready. The other two are not.

What This Means If You Keep Finance Honest

This is the section I’d ask you to read twice.

Most of the agentic commerce coverage you’ll see this year is breathless about the upside, with little of it speaking to the constituencies who actually keep finance honest: auditors, fund administrators, custodians, vendors, and compliance officers.

Those teams don’t have a playbook for this yet, because their existing playbooks all assume a human authorizer somewhere upstream.

A few questions each constituency is sitting with.

• For external auditors, the question is who signs the audit trail when a software agent initiates a transaction. Google’s AP2 cryptographic mandate framework is the first serious substitute for human authorization. Auditors should be reading those mandate structures the way they read powers of attorney today.

• For fund administrators, the question is how reconciliation works when trade count goes from hundreds per day to potentially millions across agent-originated activity. Existing NAV strike processes weren’t designed for sub-second activity at this density.

• For qualified custodians, the question is what custody actually means for an agent wallet. Once funds land on stablecoin rails, they cannot be recalled, and there’s no chargeback. The BitFinance Vaults Deep Dive covers the broader programmable-custody architecture being rebuilt around this.

• For vendors and merchants, the lesson is that agentic commerce runs on protocol endpoints, not visual checkout flows. OpenAI’s ChatGPT Instant Checkout was shelved in March 2026 after only about 30 Shopify merchants used it.

• For compliance officers, the question is what an “agent of record” looks like inside a KYC stack. American Express launched Agent Purchase Protection in April 2026, covering erroneous purchases by verified agents in its registered ecosystem. That’s the first commercial answer. Expect more.

The Risks Worth Naming

Concentration is the obvious risk, and the report makes the picture sharper than most coverage admits. 98.6% in USDC means Circle is a single point of failure for the entire settlement layer.

Sharper still: roughly 74% of agent payment volume flows through Coinbase’s chain (Base), uses a stablecoin Coinbase co-issues (USDC), and is processed by Coinbase’s facilitator. That’s the most vertically integrated payment stack assembled since Stripe built its relationship with fiat banking. The protocols are open. The infrastructure isn’t.

Regulation is the second binding risk. 3 frameworks reach enforcement in a five-week window this summer:

• MiCA’s transitional period ends July 1,

• the GENIUS Act’s implementation deadline is July 18, and

• the EU AI Act’s high-risk obligations take effect August 2.

None contain provisions for autonomous machine-to-machine transactions. The UK Competition and Markets Authority moved first in March 2026, placing full legal responsibility on businesses deploying AI agents, with fines up to 10% of worldwide turnover.

Expect other jurisdictions to follow.

Why Spend Time on This?

The Indicator Project is the work I’m doing on building agentic trading and investment solutions for individual investors, the people without an analyst team. That work is why I read the Keyrock report the morning it dropped.

The trajectory worth holding in mind is bottom-up.

Payment rails have always been rebuilt this way:
volume from below, not decree from above.

What starts as a $0.01 API call eventually pulls $50 SaaS payments onto the same settlement layer, then $500 procurement orders, and eventually flows that institutions currently assume will never leave their existing infrastructure.

The people who pay attention to the bottom of the curve now are reading the same map institutional buyers will be reading in three years. There’s an information asymmetry available, and it’s the cheap kind: the report is already public.

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Matthew Snider is the founder of Block3 Strategy Group, author of “Warren Buffett in a Web3 World,” and publisher of the BitFinance newsletter. He holds a Series 65 and MBA, and has been an active participant in digital asset markets since 2015. This article is for educational purposes only and should not be considered financial advice. Always consult with a qualified professional before making investment decisions.

Until this week, the only way to actually use it was to sit in front of it.
That changed yesterday morning.

My collaborator JMD typed a directive into a Telegram chat from his couch a three-thousand miles away, and an AI agent on the Forge wrote and committed code. I was in the kitchen making coffee. Neither of us touched the machine.

Here’s how it works, why it matters, and how you can build something similar.

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The stack, in plain English

Three pieces:

• Tailscale is a private mesh network. It strings a secure wire between any devices you own without exposing them to the open internet. No port forwarding. No public IP. No “open SSH to the world.” For us, it means our laptops and the Forge talk to each other like they’re on the same local network, even though we live a thousand miles apart.

• A Telegram bot is the chat surface. You register one through Telegram’s BotFather utility, you get an API token, and the bot sits as a member of a chat both of us belong to. By itself the bot does nothing intelligent. It’s a pipe that forwards what we type to whatever software we point at the token, and routes the response back. The intelligence sits on the other side of the pipe.

• Hermes is the brain on the other side. Hermes is an open-source autonomous AI agent framework from Nous Research, MIT-licensed, that runs as a long-running process on the Forge. When either of us sends a directive through the Telegram bot, Hermes picks it up, opens code files, executes shell commands, writes commits, manages its own permissions, logs everything it did, and reports back through the same chat. It can ask clarifying questions. It can run for hours.

In my setup, Hermes is routed through ChatGPT’s Codex as the underlying model endpoint. Hermes is the runtime, the memory layer, and the orchestrator. Codex is the brain doing the actual reasoning inside that runtime. Those two pieces together are what turn an instruction in a chat into committed code on the Forge without either of us at the keyboard.

The piece worth understanding is the memory loop. After enough tool calls on a complex task, Hermes writes the work out as a reusable skill file in plain markdown that lives on disk. Next time a similar task arrives, it loads the skill automatically and gets faster. The agent compounds. That’s what makes this fundamentally different from a chatbot session that forgets you the moment the window closes.

If you read my earlier piece on Openclaw, this is the same family of self-hosted, message-driven AI tooling, just a generation forward. Openclaw is the gateway. Hermes is the agent that lives behind the gateway and learns from what it did. The name fits the function.

In Greek mythology, Hermes carried instructions between worlds. This one does too.

Why this matters

Most “AI trading” coverage you see online is screenshots of someone asking ChatGPT to pick stocks. No infrastructure underneath. No validation. No work happening when the human isn’t typing. The user has to be at the keyboard for anything to happen, and the moment they walk away, progress stops.

What I’m describing here is the opposite of that. It’s the boring, load-bearing plumbing that has to exist before you can actually trust a system to do real work. A real machine. Real version control. An agent that holds context across sessions and writes its own skill library. Whatever happens on the autoresearch engine continues whether I’m asleep, in a meeting, on a flight, or making coffee.

The bigger unlock is collaboration. You can build trading systems alone. It’s slow, it’s lonely, and you miss obvious things because nobody is challenging you. The traditional fix is to be in the same office or to do shared screen calls, but none of that scales for a side operation between two operators with other jobs and other lives.

This setup gives us a shared workspace that is the agent itself. Either of us can direct it from anywhere. Both of us can see what it did. Hermes holds the context, the chat is the audit log, and the Forge does the work. We get the upside of working together without having to be in the same place.

How you’d build this yourself

I’ll keep this practical, because the actual setup is more accessible than it sounds.

You need 4 things.

• A persistent machine. Your Forge doesn’t have to be a Mac Studio. A Mac mini, a small Linux box, or an old desktop running headless will work. The requirements are that it stays on, it has enough memory to run an agent runtime comfortably, and you control it. Used Mac minis are cheap. Repurposed gaming PCs are cheaper.

• A Tailscale account. The free tier covers up to 100 devices. You install the client on the Forge and on every other device you want to use to reach it. That’s the entire setup. No router configuration. No firewall rules to write. If you can install an app, you can use Tailscale.

• Hermes installed on the Forge. The install is a single curl command from the Nous Research repo. It auto-configures most of what you need. You point it at whichever LLM endpoint you want to use as the brain. I’m using ChatGPT’s Codex. You could use OpenRouter, the Anthropic API, or a local model on the same machine if you have the hardware for it.

• A Telegram bot. This is the chat layer. Telegram lets you create one through their BotFather utility in about two minutes. You get an API token. You hand that token to Hermes during the install, and Hermes takes care of the rest. No script to write. Telegram is one of the 20+ messaging channels Hermes ships with out of the box.

Total cost to recreate: roughly $0 if you already own a machine and have a model API subscription. Maybe $30 a month if you’re starting from scratch and use the cheapest viable tier. The hardware is the biggest variable, and you probably already have something that works.

The whole thing takes an afternoon if you’re starting cold. The harder part is what you do with it after, not how you set it up.

What it powers

The reason I built this isn’t the chat. The chat is the interface. The reason is the autoresearch engine that sits behind it.

The engine takes a strategy idea and runs it through hundreds or thousands of parameter and regime variations. It applies our multiple-gate validation framework I’ve written about before. It tells me what survives statistical scrutiny and what doesn’t.

That second piece, the trial count, is the one that matters most. Most published Sharpe ratios are meaningless because the publisher doesn’t disclose how many trials they ran to get there. Mine runs the trials explicitly and applies the haircut.

What does that mean for you?

It means the indicators and strategies I write about going forward will have actually been validated, not just back-of-the-envelope plausible. It means I can share work the engine has completed, not just hypotheses. It means the cycle from interesting idea to tested result you can act on gets significantly shorter, because Hermes never sleeps and the machine never logs off.

Here’s a glimpse of the dashboard the agent has been working on.

The first screenshot is the intake form where a new strategy idea gets captured. The second is the Kanban view of the pipeline, showing where every strategy sits today.

That’s the work that needs autoresearch time, which is exactly why getting the remote-control piece working this week mattered. The bottleneck was never ideas. The bottleneck was machine time, and machine time only counts if the machine is actually running.

Where it can break

Honest part. An agent that can pilot your machine is a real security surface. Tailscale plus tight permission scoping plus a private chat with two known humans is the floor, not the ceiling. Anyone deploying something like this without that posture is asking to lose the machine.

The agent also doesn’t do everything. It’s excellent at coding tasks, file edits, running scripts, and checking the output. It’s not running autonomous trades or making decisions without review. The pipeline is built so a human signs off at each gate. That’s intentional. I’m not interested in giving an LLM the ability to move money without me reading what it did first.

Setup takes some focused time. Maybe an afternoon if you’re starting cold. After that it just runs.

If you decide to try this and get stuck, reply to this post or hit me on Substack chat. I’ll point you somewhere useful. The reason I’m writing it up this way is that I think more retail quants should be running real infrastructure, not just clicking around in apps. The tools are finally cheap enough and accessible enough that there’s no good excuse anymore.

Want to be part of what we’re building?

I’m building the early cohort for when the Discord opens and the first indicators ship. If you want a seat, this is where to claim one.

Interested? Fill out the 30-second interest form here. 👈

moving right along…

This Week in 2 Mins

$1.75 Trillion Is About to Reprice Six Industries (May 19)

SpaceX is reportedly filing for IPO on June 12 at a $1.75 trillion valuation, which would be the largest public listing in history. I used my undergrad-era Virgin Galactic memory as a reminder that getting the timeline wrong on a real narrative is how investors lose money. The actual investable space economy is bigger than the rockets and breaks into six layers:

• Launch, in-orbit infrastructure

• Satellite services

• Communications

• Manufacturing and supply

• Commodities and power (the bedrock layer)

The bedrock layer is the one nobody is pricing in. Names with real cash flow today, like Iridium, BWXT, and MP Materials, are where the durable bets live. Most of the heat is on the higher-variance names at the top of the stack. The lesson from 2011 was that the businesses underneath the headline outperformed the headline itself. The same is probably true now.

Read the full article here.

5 Crypto Risk Management Rules That Actually Work (May 21)

A collaboration with ! Most crypto traders learn risk management the hard way, and then learn the wrong lesson from it. Five rules that actually work, drawn from how professional portfolio managers run money: don’t risk more than 1-2% on a single trade, set your stop before you enter rather than after, cap the whole portfolio not just individual trades, shrink position size when volatility rises, and preserve capital above everything else.

The core insight binds all five together. Capital you preserve compounds. Capital you lose has to be re-earned at exponentially worse odds. A 50% loss requires a 100% gain to recover. A 90% loss requires a 900% gain. Pick two of the five rules and apply them this week. The trader who follows two rules consistently will outperform the trader who knows all five and applies none of them.

Read the full article here.

Winners & Losers This Week

Winners 🏆

• Kevin Warsh was sworn in Friday as the 17th Fed Chair after a 54-45 Senate vote, the most divisive Fed chair vote in history. The Dow set a record close at 50,580 the same day, and the S&P extended its weekly winning streak to eight, the longest since December 2023.

  

• Nvidia delivered a beat-and-raise midweek that dragged the AI-linked names along for the ride. SoftBank rallied two days straight and added roughly $61B in market cap, one of the largest two-day gains in Tokyo Stock Exchange history.

• OpenAI and SpaceX both filed IPO paperwork in the same week. Both are expected to be among the largest U.S. IPOs ever. The 2026 calendar is now genuinely historic.

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Losers 📉

• Long-duration Treasury holders. The 30-year yield touched 5.197% midweek, the highest in over a year, pressuring bond prices and rate-sensitive equities before easing late in the week.

  

• Bitcoin spent the week stuck between $76K and $78K, well off the $82K from the prior week. A $563M liquidation cascade on May 18 reset positioning, and the BTC-as-macro-hedge narrative took another hit when a high-profile billionaire investor disclosed he sold most of his bitcoin because it didn’t behave like a hedge during the geopolitical stress.

• Walmart, Amazon, and Nvidia (the stock, not the print) closed Friday in the red despite the broader tape rallying, a reminder that index records can mask narrow leadership.

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On Deck

Memorial Day shortens the week, but Friday is loaded.

• Monday: U.S. markets closed for Memorial Day. 🇺🇸🦅 This means I’ll take my annual trip to the Duke Golf Course.

  

• Friday: PCE inflation, the second revision to Q1 GDP, personal income and spending, advanced trade balance, and Chicago PMI all hit before the open. This is Warsh’s first major inflation print as Fed Chair, and the tape will price the read accordingly.

• Retail and enterprise earnings: Salesforce, HP, Costco, Dell, Marvell, Best Buy. Read the consumer prints for actual demand signal, the enterprise prints for AI capex commentary.

• Crypto and regulatory: Trump’s executive order kicked off a 120-day Fed review of whether crypto firms should get direct access to Federal Reserve payment services, and the CLARITY Act still has dozens of amendments pending. Slow-burn stories, but next week could surface headlines.

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Matthew Snider is the founder of Block3 Strategy Group, author of “Warren Buffett in a Web3 World,” and publisher of the BitFinance newsletter. He holds a Series 65 and MBA, and has been an active participant in digital asset markets since 2015. This article is for educational purposes only and should not be considered financial advice. Always consult with a qualified professional before making investment decisions.

If you're new here from one of our publications, welcome. The piece below is one cohesive argument we both stand behind, not two essays stitched together.

******

Most crypto traders learn risk management the hard way. They take a big position, the market moves against them, they freeze, and by the time the loss becomes real, they’ve already learned a lesson that cost more than it had to.

Between the two of us, we’ve watched this play out for more than fifteen years. The traders who survive multiple cycles share something most of the rest don’t. They built their risk discipline before they needed it.

The five rules below come from how traditional portfolio managers, hedge fund risk officers, and family office allocators actually run money. They aren’t complicated. They aren’t new. They work because they all derive from a single insight.

Capital you preserve compounds.
Capital you lose has to be re-earned at exponentially worse odds.

That second part is the one most retail investors never internalize. The math is harder than it looks, and it’s the reason every rule below exists.

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RULE 1: Don’t Risk More Than 1-2% on a Single Trade

The Warren Buffett Mantra: "Risk comes from not knowing what you are doing."

Professional portfolio managers almost never let one trade put more than 1-2% of their total capital at risk. In crypto, it’s common to see people put 20% or 30% into one altcoin because the conviction feels strong. Conviction is not a position-sizing model.

Crypto moves fast and drops hard. A normal 50% drawdown on a large position can erase months of gains in a single week. The 1-2% rule isn’t about being scared. It’s about staying alive long enough for your winners to actually work.

The math is simple. Your max loss on any trade should be a fraction of your account, not a fraction of the position. Once you decide the max loss, the position size becomes a calculation rather than a feeling.

Position Size = (Account × Risk %) ÷ Stop Distance %

Run the numbers for an account willing to risk 1% per trade with a 20% stop:

Most retail crypto traders size by gut feel and then wonder why a single bad trade wipes out three months of gains.

The fix is to size first, then enter. Ultimately the goal is to make sure you can stay in the game because no single trade wrecks the entire portfolio.

RULE 2 : Set Your Stop Before You Enter, Not After

The Warren Buffett Mantra: “The most important thing to do if you find yourself in a hole is to stop digging.

Traditional investors rarely enter a trade without a clear plan for both downside protection and profit taking. In crypto, many people hold with diamond hands until they’re down 80-90%, then panic-sell at the bottom. That looks like conviction from the outside, but it functions like denial.

A real plan has three parts. Where you exit if you’re wrong. Where you take partial profits if you’re right. What signal would change your mind before either trigger fires.

Set the stop based on a technical level, a volatility band, or the moment the original reason for the trade no longer applies. Stops aren’t predictions about where the market will go. They’re admissions that you can’t predict, and you’d like to be wrong cheaply.

The other piece worth setting before the trade is the risk-reward ratio. If you’re risking 20% to make 20%, you need to be right more than half the time just to break even after fees. If you’re risking 20% to make 60%, you can be wrong twice as often as you’re right and still come out ahead. Look for setups where the math favors you before the trade even starts.

RULE 3: Cap Your Whole Portfolio, Not Just Each Trade

Warren Buffett Mantra: "The riskiness of an investment is not measured by beta but rather by the probability of that investment causing its owner a loss of purchasing power over his contemplated holding period."

Serious investors control risk at the portfolio level, not just the individual trade level. That means hard rules like a maximum 10-20% drawdown before reducing exposure across the board. Limits on how much capital can sit in any one sector or narrative. Caps on correlated assets.

Crypto traders often pile into whatever narrative is hot, then wonder why everything moves together when sentiment turns. Holding eight Layer-1 tokens isn’t diversification. It’s one bet wearing eight different costumes.

Correlation is the silent killer in crypto. During a normal market, an altcoin bag might look diversified. During a real selloff, everything trades like one position. The portfolio-level cap is what protects you when correlation goes to 1.0, which it always does at the worst possible moment.

A 25% allocation to crypto across four uncorrelated assets behaves very differently than a 25% allocation to four assets that all crash together. The number on the position sheet is not the number on the risk sheet.

RULE 4: Shrink Position Size When Volatility Rises

Warren Buffett Mantra: "Be fearful when others are greedy, and greedy when others are fearful."

When markets get crazy, professional traders make their positions smaller. In crypto, when things get volatile, most retail traders do the opposite. They add leverage because they think the moves will be faster.

Faster moves with leverage means faster liquidations. The reason professionals shrink positions during high-volatility periods is the same reason airlines lower their flight altitude in turbulence. The cost of being wrong gets higher when conditions get rougher.

A simple way to scale positions to volatility is to look at average true range, or ATR. When ATR doubles, your position size should roughly halve to keep the dollar risk constant. This sounds like extra math, but in practice it’s a single calculation per trade. It’s also the difference between surviving a volatile week and getting carried out.

The trader who sizes the same in calm markets as in panicked ones is taking double the risk during the panic. The dollar amount on the position sheet looks identical. The actual exposure is not.

RULE 5: Preserve Capital First. Always.

Warren Buffett Mantra:
Rule #1: Don’t lose money.
Rule #2: Don’t forget the first rule.

Most crypto traders focus on maximum upside. Experienced investors focus first on not going to zero.

The question to ask before every position is whether you can sleep with it. If the answer is no, the position is too big. Cut it until you can sleep.

The traders who make it through three or four full cycles all share this discipline. They keep meaningful cash or stablecoin reserves, often 20-50%, so they’re ready when the next opportunity arrives and protected when the next selloff does.

The reason capital preservation matters more than upside capture is the recovery math. This is the chart most retail investors have never been shown.

A 50% loss requires a 100% gain to recover. A 75% loss requires a 300% gain. A 90% loss requires a 900% gain. The math gets exponentially harder, not linearly harder.

Every rule above exists to keep you on the top rows of that table, not the bottom ones.

The Real Reason These Rules Work

None of the rules above are complicated. None of them are new. The reason they keep showing up in serious portfolio management is that they’re not really about predicting markets.

They’re about surviving them long enough for the rest of your edge to matter.

Most crypto traders don’t lose money because they pick bad assets. They lose money because they size positions too large, hold too long, and freeze when conditions change. The discipline of risk management is what separates the traders who are still here after five years from the ones who aren’t.

Pick two of the five rules above and apply them this week. Not all five. Two. The trader who actually follows two rules consistently will outperform the trader who knows all five and applies none of them.

The market will always be volatile. Your process doesn’t have to be.

Trade safe!

Mari and Matthew

Share BitFinance with Matthew Snider

About the Authors

writes Mari’s Crypto Alpha, helping busy professionals navigate crypto markets. Twelve years in crypto, government crypto advisor and lawyer, raised over $100M from Solana, Animoca, Sequoia, Polygon, and Delphi.

Matthew Snider is the founder of Block3 Strategy Group, author of “Warren Buffett in a Web3 World,” and publisher of the BitFinance newsletter. He holds a Series 65 and MBA, and has been an active participant in digital asset markets since 2015. This article is for educational purposes only and should not be considered financial advice. Always consult with a qualified professional before making investment decisions.

This article is for informational and educational purposes only and does not constitute investment, financial, legal, or tax advice. Securities mentioned involve risk and may not be suitable for all investors. Past performance is no guarantee of future results. Readers should conduct their own due diligence or consult with a licensed financial advisor before making any investment decisions.

That was 2011. Virgin Galactic eventually went public, then flew about a dozen paying customers, then watched its stock fall more than 99% from peak.

The promise was real, but the timeline was wrong by about a decade or more.

I tell you this because the space narrative is back, and it’s louder than it has ever been.

SpaceX files for IPO on June 12 at a reported $1.75 trillion valuation, which would make it the largest public listing in history.

Wall Street is going to spend the next six months telling retail investors that space is the next frontier (not just the final one!). Most of that coverage will focus on the rocket companies, because rockets are easy to photograph….but today, let’s dive deeper into the ecosystem of companies building this industry literally from the ground up.

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A Map of the Coming Wave

The actual investable space economy is bigger than the rockets, and it’s worth understanding before the SpaceX listing repackages every public name in the sector.

Think of the space economy like building a city from scratch.

You need transportation to get there, builders once you arrive, services that earn revenue once the city is operational, communications to tie everything together, parts suppliers feeding the whole thing, and underneath all of it, the raw materials and power that make the city work.

Six layers. Each one has public companies you can actually own today.

Here’s the 6-layer stack. Pay particular attention to companies the bedrock layer. To me, this feels like the sector nobody is pricing in. 👀

LAYER 1: Launch

Notable pics: Rocket Lab (RKLB)

Launch is the highway system of space. Nothing else works without it. SpaceX owns roughly 60% of global launch market share and is filing for IPO. Rocket Lab is the only public alternative with a credible medium-lift vehicle in development, called Neutron, targeting first flight later this year.

Rocket Lab reported $200 million in Q1 2026 revenue, up 64% year over year.

Backlog stands at $2.2 billion, more than double a year ago. Roughly 68% of revenue now comes from satellite components and spacecraft, not launch itself, which means the company is becoming a vertically integrated space platform rather than a pure launch provider.

The valuation already prices in Neutron flying on schedule, so any timeline slip will compress the stock quickly. Defense exposure through the Golden Dome interceptor program adds an upside catalyst.

Oh this? Nothing…just the stock trading at $7 per share 2 years ago.

LAYER 2 : In-Orbit Infrastructure

Notable pics: Redwire (RDW), Intuitive Machines (LUNR)

Once you’re in orbit, somebody has to build the platforms, the solar arrays, the landers, and the manufacturing facilities that actually operate up there.

Redwire builds parts on roughly half the missions you’ve read about. Q1 2026 revenue grew 58% to $97 million, with a backlog of $498 million. Book-to-bill of 1.92 means new contracts are arriving nearly twice as fast as revenue is being recognized.

The company is still losing money, and the share count keeps expanding, so this is a higher-variance bet that hinges on Edge Autonomy integration working.

Intuitive Machines is the only public company that has actually landed on the moon. Twice. NASA’s lunar program runs through commercial partners, and LUNR has captured multiple Commercial Lunar Payload Services contracts including a $180 million South Pole delivery booked in March.

Full-year 2026 revenue guidance is $900 million to $1 billion. The stock has run 132% in six months, which means sentiment is doing a lot of the work.

LAYER 3: Satellite Services

Notable pics: Planet Labs (PL), AST SpaceMobile (ASTS)

Satellites earn money in two ways; either by selling the data they collect, or by selling connectivity.

Planet Labs runs an Earth imaging constellation with more than 200 satellites and posted record revenue of $308 million in 2025 against a $900 million backlog. Recurring contract value is 98% of revenue, which is the kind of utility-style economics that gets analysts excited.

AST SpaceMobile is more speculative. The company is building space-based cellular broadband that connects directly to standard smartphones from orbit. If it scales, every phone on Earth becomes a satellite phone with no special hardware. That’s the bull case. The bear case is that the deployment timeline keeps slipping and the cash burn is significant.

From a portfolio perspective, it would make sense to treat this as a venture-style position and not a core holding due to the uncertainty associated with this level in the stack.

LAYER 4: Communications & Operations

Notable pics: Iridium (IRDM)

Every other layer depends on satellite networks that move data between space and Earth. Iridium operates the only constellation covering 100% of the planet, with predictable subscription revenue from defense, maritime, aviation, and IoT customers.

This is the boring, cash-generative name on the list and the kind of business Buffett would actually look at.

Globalstar is being acquired by Amazon for $11.6 billion to power its Project Kuiper rival to Starlink, with Apple’s Emergency SOS feature riding along. The deal closes pending FCC review. Iridium is now the largest independent public name in this layer.

LAYER 5: Manufacturing & Supply

Notable pics: L3Harris Technologies (LHX), Northrup Grumman (NOC), RTX Corporation (RTX), Lockheed Martin (LMT)

Defense primes design and build the satellites, rocket motors, and avionics that everyone else uses. The thesis here is diluted because space is a fraction of total revenue.

• L3Harris build classified comms and satellites used by the U.S. Dept. of War.

• Northrop Grumman builds rocket motors.

• RTX builds GPS satellites…oh, and hypersonic weapons for what that’s worth.

• Lockheed Martin runs the largest classified space programs on Earth.

These names give you space exposure wrapped inside a much broader defense portfolio, which is either a feature or a bug depending on what you actually want to own.

LAYER 6: Commodities & Power

Notable pics: MP Materials (MP), BWX Technologies (BWXT).

This is the layer that almost every space investment article ignores, and it’s the one I find the most compelling.

• Every satellite needs magnets.

• Every magnet needs rare earths.

• Every off-world data center, lunar base, or deep-space mission needs nuclear power because solar alone doesn’t cut it past a certain distance or in shadowed regions.

MP Materials operates the only active rare earth mine in the United States.

The Department of War took an equity stake in 2025 and established a 10-year price floor of $110 per kilogram on the key magnet material, which removes commodity price risk from the business model.

Apple committed $500 million for domestically made magnets. Q1 2026 revenue grew 49%, with magnet production set to launch in the second half of this year. Government-aligned, structurally favored, and the only at-scale operator in a market China has historically dominated.

BWX Technologies supplies the reactors that power every US Navy submarine and aircraft carrier. That naval nuclear business throws off predictable cash flow that funds the company’s space work, which includes the Pele microreactor for the Department of War and the DARPA DRACO nuclear thermal propulsion program.

Q1 revenue grew 26%, EBITDA grew 14%, and the company raised full-year guidance. Backlog stands at $8.7 billion. This is the cleanest cash-generative name on the entire list, and the regulatory moat around naval nuclear is essentially impossible to replicate.

How to Actually Use This

Here’s what fifteen years between space narratives taught me.

The companies that survive long enough to matter are the ones with real cash flow today, not the ones selling a compelling future. Virgin Galactic had the better story in 2011. Aerospace primes and satellite operators that nobody talked about had the better business.

The same is probably true now. Two of the six layers, communications and commodities, are where cash-generative businesses sit with structural tailwinds. BWXT, MP Materials, and Iridium are the names worth deeper diligence if you want exposure without betting on timelines. The other layers are higher variance, which is fine if position size matches the conviction.

Note the “The Buffett zone” in the upper-right. Most of the heat in this sector lives in the upper-left.

If I had to build a starter basket from this list, it would lean heavily toward layers four and six, with smaller positions in layer two for the lunar economy optionality. Rocket Lab is a fine name in layer one, but the multiple already reflects most of the upside.

Buffett Framework Question: Which of these companies would I still own if the SpaceX IPO underperforms and the space narrative cools for three years? The answer narrows the list quickly to the names with cash flow today. That’s not a coincidence. That’s the lesson.

Space is going to be a real economy. It’s also going to take longer than the headlines suggest. Both things can be true. Position accordingly.

The biggest IPO in history is going to make space feel like it just became investable. It didn't. It's been investable for years. The companies underneath the rockets have been building real cash flow while the headlines waited for SpaceX.

When the noise hits on June 12, remember which layer the bedrock is on.

Until next time!

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🛑 REMINDER 🛑

Quick reminder of what we’re building. Live indicators. The research behind them. The methodology taught alongside the signal. A small room where you leave knowing how the work actually gets done

I’m building the early cohort for when the Discord opens and the first indicators ship. If you want a seat, this is where to claim one.

Interested? Fill out the 30-second interest form here. 👈

Sources:

• Q1 2026 earnings releases from Rocket Lab, Redwire, BWX Technologies, MP Materials, and Intuitive Machines. SpaceX IPO reporting from Reuters, Bloomberg, and Fortune.

• Amazon-Globalstar transaction announcement, April 14, 2026.

• Starcloud Series A coverage from Data Center Dynamics, March 2026. Department of War / MP Materials Price Protection Agreement, July 2025.

• Apple / MP Materials $500 million commitment, August 2025.

• NASA Commercial Lunar Payload Services contract awards documentation.

• BWXT / DARPA DRACO and Pele microreactor program announcements.

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Matthew Snider is the founder of Block3 Strategy Group, author of “Warren Buffett in a Web3 World,” and publisher of the BitFinance newsletter. He holds a Series 65 and MBA, and has been an active participant in digital asset markets since 2015. This article is for educational purposes only and should not be considered financial advice. Always consult with a qualified professional before making investment decisions.

This article is for informational and educational purposes only and does not constitute investment, financial, legal, or tax advice. Securities mentioned involve risk and may not be suitable for all investors. Past performance is no guarantee of future results. Readers should conduct their own due diligence or consult with a licensed financial advisor before making any investment decisions.

It’s the first step in an 18-month plan that doubles as my answer to a question more knowledge workers should be asking themselves: what’s my AI hedge?

I want to walk through what I’m doing and why, because some version of it is relevant to more people than the headline suggests.

The AI Moat Almost Nobody Talks About

AI is going to compress a lot of what people get paid for in financial services. Full stop.

Analyst tasks, modeling, research write-ups, first drafts of nearly everything. I use AI extensively in my own work, so this isn’t speculation, it’s observation. The 80% of a typical knowledge-worker job involving drafting, summarizing, and structured analysis is getting commoditized in real time.

What AI doesn’t change is licensing.
Treat professional licenses like a career “moat”.

• You can’t sell securities without a license.

• You can’t give investment advice for compensation without an IAR registration.

• You can’t solicit futures customers without an AP registration.

The regulatory perimeter around financial services is one of the few moats genuinely insulated from AI commoditization, because the moat is statutory rather than technical.

Software can’t pass a Series 7 on your behalf and it can’t file your U4.

The administrative 80% of the work gets automated. The 20% that requires the credential becomes a higher proportion of where my time goes, and the value of that 20% goes up rather than down. In a heavily AI-disrupted services market, being unlicensed means being replaceable, while being licensed makes you one of the people the AI runs through rather than around.

This is, by some distance, the most durable career hedge I see in front of me. If you’re in professional services and not thinking about your work in these terms, you should be.

The Lucky Part

Here’s the fortunate alignment. I’m a sucker for an educational challenge.

The MBA was a stretch I genuinely enjoyed. Studying for the Series 65 was the same kind of fun. All I kept hearing on crypto twitter was influencers and talking heads saying “this isn’t financial advice” - and I thought I could differentiate myself by passing a rigorous exam that allowed me to do just that.

There’s a particular satisfaction in sitting down with hard material, working it until it clicks, and walking out genuinely more capable. People train for marathons. I sign up for exams. The wiring is the same.

So this isn’t me white-knuckling through a defensive credentialing program because I’m worried about AI. I’m doing something I’d want to do anyway, and the fact that it happens to be one of the most durable AI hedges available is a bonus.

The 18-Month Plan

By end of 2026:

• SIE (registered last night)

• Series 7 (general securities representative)

• Series 63 (state law for BD agents)

• Series 3 (commodities and futures)

By end of 2027:

• CAIA Level I and Level II (Chartered Alternative Investment Analyst)

• FRM Part I and Part II (Financial Risk Manager)

Credential Count: 6
Time to Goal: 18 months
Total Cost (incl. study materials): ~$11,000

What Each One Does and Why I Want It

• The SIE is foundation. Anyone over 18 can take it without sponsorship. I’m taking it because it unlocks the others.

• The Series 7 closes the brokerage-side gap. When a client wants help structuring a Reg D offering and placing the resulting interests, currently I can handle one half cleanly. The 7 makes the other half mine.

• The Series 63 is the state law exam that activates the Series 7 in your home state. It’s the most accessible exam in the FINRA stack. You can self-enroll without sponsorship, and heavy overlap with the Series 65 makes it the fastest of the group for me.

• The Series 3 is commodities and futures. Half the crypto strategies I look at touch this. BTC basis trades, ETH funding rate arbitrage, anything with a futures leg; e.g. Perpetual Futures. (read more here)

• The CAIA is the alternative investments designation. Most of what I do at Block3 is alts-adjacent or alts-native. The CAIA puts an institutional stamp on a body of work I’ve been doing for years managing hedge funds and building investment vehicles. It makes a powerful career complement when paired with the Series 7.

• The FRM is the risk management designation. For someone publishing investment research and helping family offices and PMs evaluate digital asset exposure, FRM is the credential that says I think about downside the way they do. Oh, and last time I checked…crypto and blockchain tech is still risky. Having a framework to help orgs manage risk is going to be huge.

Each one maps onto a conversation I already have. The credentials put institutional language behind work I’m already doing, and each adds a layer AI can’t strip away.

The Accredited Investor Unlock Most People Miss

Here’s something underdiscussed and relevant if you’re reading this and thinking “interesting, but not for me.”

In 2020 the SEC expanded the accredited investor definition. Net worth and income are still the common qualifying paths, but holders of the Series 7, Series 65, or Series 82 in good standing now qualify on credential alone.

No $200K income or $1M net worth requirement.

Being an accredited investor matters because accredited status unlocks Regulation D private placements, pre-IPO secondaries, hedge fund participation, venture deals.

The Anthropic and SpaceX secondaries everyone has been trying to get into are accredited-only. Most people qualify through income or net worth. Licensed professionals can qualify through holding the license itself.

If you’re an early-career professional, or a serious investor without the income to clear the bar, the Series 65 is a roughly $400 path to accredited status.

One of the most underrated arbitrages in personal finance. Bar none.

Cost Reality + Honest Gaps

A two-year credential stack at $10K to $12K is real money. It’s also less than 12% of what a decent MBA program costs today, and the opportunity cost on a two-year residential MBA adds another six figures in foregone income.

I have an MBA. I’d recommend it for the networking, not the credentials. If you like education, MBAs are great. If you like people, MBAs are great.

Candidly, there are faster, more direct ways to become a financial professional, though, and business school isn’t the right tool if the specific goal is operational fluency in financial services.

The Gaps: What this credential stack doesn’t make me…

• A CFA charterholder (buy-side equity research).

• A CFP (personal financial planning).

• A JD or CPA (better partnered with than competed against).

Specialization rocks.

For Anyone Considering This Path

Some of these exams require firm sponsorship. The Series 7 and Series 3 in particular need an affiliated firm willing to register you. That’s a real barrier.

What isn’t a barrier: starting to study. The SIE, Series 65, and Series 63 you can all take on your own - you don’t even need a college degree!

By the time you’re ready to ask a firm to bring you on, you can demonstrate not just interest but real preparation. In financial services, people who actually do what they say they will do are rarer than you’d expect.

If you’re reading this with even mild anxiety about AI displacing your work, don’t wait. Start with the exams you can take on your own. The Series 65 in particular is a thirty-hour commitment that pays off in both AI insulation and accredited investor status.

I’ll be writing about this periodically over the next 18 months.
If you’re on a similar path, I’d love to hear about it.

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This Week In 2 Mins

I Found a Token That Acts Like a 30-Year Mortgage on AI Compute (May 12)

Erik Voorhees's privacy-first AI platform Venice has built two of the more coherent token mechanics in the AI-crypto category.

VVV gives stakers proportional access to the platform's inference capacity at 14-18% yield, while DIEM represents $1/day in API credit in perpetuity. Think of this like a power purchase agreement but applied to AI compute.

Buy-and-burn engine, 42% of supply already burned, $700-800M market cap, real revenue. Article also flags three other AI plays I'm watching: Bittensor (TAO), NEAR Protocol, and Virtuals (VIRTUAL).

What are your pics in the AI/crypto sphere?🤔

Read the full article here.

Ten Years Ago, Crypto Built the Most Important Derivative of the Decade
(May 14)

On May 13, 2016, BitMEX shipped the first perpetual futures contract with no expiration, no settlement, no precedent in 200 years of derivatives history.

A decade later it's a $7.24T market.

This article walks through the funding rate mechanic (the "dog on a leash" metaphor), why the design works, how sophisticated traders use perps for yield rather than leverage, and what's coming next as the contract spreads to oil, gold, S&P 500, and tokenized real-world assets.

Hyperliquid runs 44% of perp DEX volume with a $640M annualized fee run rate and 97% buy-and-burn. JPM, Grayscale, Bitwise, and VanEck have all moved into the space.

Are you using perps to trade? I want to know!

Read the full article here.

Winners 🏆

• CLARITY Act. Senate Banking Committee 15-9 bipartisan vote on May 14, headed to the Senate floor. Two Democrats (Gallego, Alsobrooks) joined all Republicans. First real bipartisan progress on U.S. crypto market structure after four months of negotiation gridlock. Legislative path still requires merging with the Agriculture Committee version and resolving the ethics provision, but the political momentum changed direction this week.

  

• Q1 earnings season. S&P 500 blended earnings growth came in at 27.1%, the highest growth rate since Q4 2021 (32.0%) and the 6th consecutive quarter of double-digit year-over-year earnings growth. 84% of companies that have reported beat EPS estimates, above the 5-year average of 78%. Communications Services, IT, Consumer Discretionary, and Materials led growth. Whatever you think of valuations, the underlying corporate earnings story is doing its job.

• Energy sector. Energy was the sole sector with gains on Friday, rising 1.6% as the post-Iran War oil spike continues to ripple through markets. With one airline CEO noting the jet fuel crisis is about to hit airlines worse than Covid and the Strait of Hormuz logistics still unwinding, energy looks like the obvious risk-off hedge for a market increasingly nervous about an inflation re-acceleration.

Losers 📉

• Semiconductors and AI hardware. Friday’s profit-taking was brutal across the AI rally’s biggest names. Intel retreated more than 6%, while Advanced Micro Devices and Micron Technology lost 5.7% and 6.6%, respectively. Nvidia dropped 4.4%, while Cerebras Systems — which surged 68% Thursday after it began trading on the Nasdaq — shed 10%. The trigger was the Trump-Xi summit ending without major breakthroughs, but the deeper read is that the group is being called out for an unsustainable recent move. Worth watching whether this is a healthy reset or the start of something bigger.

  

• Small caps. The Russell 2000 lost more than 2% in midday Friday trading. If that holds through session close, it would mark the index’s worst day since November... The Russell 2000 is now down more than 2% on the week, putting it on track to snap a seven-week winning streak. Small caps had been the breadth story underneath the mega-cap-led rally. Breaking the streak matters because it suggests the rally’s been narrower than it looked.

• Rate cut expectations. The Fed funds futures market repriced hard this week. Traders now see the Fed raising rates for its next move, a complete reversal from where positioning sat a month ago. “Ten of the last 12 recessions were preceded by a spike in oil”, Dan Niles noted on CNBC Friday. The Fed’s hands look increasingly tied between oil-driven inflation and growth concerns, and the cost of waiting is no longer obvious.

  ---

Watch this coming week (May 18-22)

• Retail earnings week. Walmart, Home Depot, Target, Lowe’s, and TJX are expected to report. The K-shaped consumer thesis (high-end resilient, low-end pressured by gas prices) gets its biggest test of the cycle. Watch the guidance more than the prints. Retailers cutting full-year outlooks would be the cleanest signal that the consumer is finally cracking.

• NVIDIA earnings (likely late May). The most important single print in equities, full stop. After Friday’s semis selloff, the bar is higher than it’s been in two years. Beat-and-raise gets the AI rally back on track. Anything less reframes the entire group as overextended.

• Oil price direction. Brent and WTI behavior is now the dominant macro variable. It will be months before the oil disruption rights itself, as it takes weeks for ships sailing out of the Strait of Hormuz to reach destinations in North America, Europe or East Asia, and investors don’t expect oil prices to return to pre-war levels. Sustained levels above current marks keep pressure on the Fed and the consumer. A break lower opens room for the cut narrative to come back.

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Quick reminder of what we’re building. Live indicators. The research behind them. The methodology taught alongside the signal. A small room where you leave knowing how the work actually gets done

I’m building the early cohort for when the Discord opens and the first indicators ship. If you want a seat, this is where to claim one.

Interested? Fill out the 30-second interest form here. 👈

Matthew Snider is the founder of Block3 Strategy Group, author of “Warren Buffett in a Web3 World,” and publisher of the BitFinance newsletter. He holds a Series 65 and MBA, and has been an active participant in digital asset markets since 2015. This article is for educational purposes only and should not be considered financial advice. Always consult with a qualified professional before making investment decisions.

No expiration date.
No settlement.
No precedent in 200 years of derivatives history.

The Nobel-winning economist Robert Shiller had floated the theoretical idea in the 1990s, but nobody had built one. On May 13, 2016, Arthur Hayes and the BitMEX team shipped the first perpetual futures contract.

A decade later, it has become one of the most-traded financial instruments on the planet. The global perpetual futures market hit $7.24 trillion in January 2026, up from $4.14 trillion two years earlier. Decentralized exchanges alone processed roughly $2.4 trillion in Q1 of this year.

Most people I talk to have heard the term and have no idea what it actually means. Worth fixing. Here’s the primer I wish I had when I first started reading about Hyperliquid, Aster, and Euphoria.

BUFFETT FRAMEWORK QUESTION

“Do I understand this instrument well enough to use it intelligently, or stay away from it intelligently?” For perpetuals, most retail investors can’t answer either way. That’s a gap worth closing.

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Start with a regular future

Forget crypto for a second.

A “future” is a contract that says:

• I agree to buy something at a fixed price on a fixed date.

• If the price goes up, I profit because I locked in a lower price than the market.

• If the price goes down, I lose because I locked in a higher price than the market.

Buffett has used this exact structure for decades when Berkshire’s railroads and utilities lock in commodity exposure. Other analogies might include:

• A corn farmer sells corn forward in spring to lock in his fall price.

• An airline buys jet fuel forward to know what it will pay in six months.

• CME crude oil or soybean contracts on the trading floor in Chicago.

Same structure, different underlying, but two important features matter here.

1. The contract expires.

2. Settlement happens at expiration.

If you want to keep your exposure beyond expiration, you roll the position into the next contract, which costs money in spread and creates tracking error against the underlying.

That cycle has worked fine for 200 years because traditional markets close.

Why this structure breaks in crypto

Bitcoin doesn’t close. It trades at the same intensity at 3am on a Sunday as it does at 10am on a Tuesday. A quarterly contract that settles on a Friday afternoon is awkward for an asset class that never sleeps. The rollover friction adds up fast for anyone who actually wants leveraged exposure for months at a time.

That was BitMEX’s problem in 2016.

no stopProfessional traders wanted leveraged Bitcoin exposure without rolling a quarterly contract every three months. The obvious solution was a contract that just keeps going. The non-obvious problem was that if the contract never expires, nothing forces its price to converge with the spot market. Without convergence, you have two prices for the same asset, and arbitrageurs can’t reliably close the gap.

How to think about the “funding rate”

Here’s the metaphor that does most of the work.

Think of a perpetual contract as a dog on a leash.
The spot price is the owner.
The funding rate is the leash.
The dog can wander left or right, but every tug brings it back to the owner’s side.

As a finance nerd, I find the mechanism quite elegant.

Every eight hours, longs and shorts swap a small payment. The size and direction depend on the gap between the contract price and the spot price.

When the perpetual trades above spot, longs pay shorts. That payment makes it expensive to stay long and profitable to short, which pulls the contract price back down. When the perpetual trades below spot, the flow reverses. Shorts pay longs, the cost of being short rises, and the contract gets pulled back up.

The doggo can drift but it can’t escape (hopefully!). The further it tries to wander, the harder the owners pulls it back in line.

This single design choice is the entire innovation.

It replaces the convergence-by-expiration mechanic that has anchored futures markets since the 1800s with a continuous, market-driven payment system. Arbitrageurs do the heavy lifting. When the perpetual drifts above spot, sophisticated traders buy spot, short the perpetual, and collect the funding rate as a yield. That trade is mechanical and capital efficient. It’s also what Ethena built a $5 billion synthetic dollar around on Ethereum.

BitMEX’s own data shows extreme funding rates have dropped 90% since 2016 as more arbitrage capital has shown up. The market is doing what markets do when a mechanism works.

Smart money has filled the gaps, and the contract has become more boring and more reliable in the process.

What perpetuals actually let you do

Four things, and they’re the reasons the product spread:

• 24/7 markets matched to the underlying asset, with no closing bell and no overnight gap risk for assets that trade continuously.

• No rollover. A position opened today can stay open for years without paying friction every quarter.

• High capital efficiency. Leverage on most venues runs 10x to 100x. Some go to 1000x. That’s both the appeal and the destruction mechanism, depending on who’s using it.

• Synthetic exposure to almost anything. If you have a reliable price feed, you can build a perpetual on it. Bitcoin, oil, gold, the S&P 500, a tokenized treasury bill, a basket of memecoins. The collateral and the underlying don’t need to live on the same chain or in the same asset class.

  ---

The business model behind perpetual exchanges

Perpetual exchanges make money the same way every other exchange does. Maker-taker fees, typically 0.01% on the passive side and 0.035% on the aggressive side.

The volume is what makes the math work.

Hyperliquid, built on its own Layer 1 blockchain, is currently the largest decentralized perpetual exchange in the world. Roughly 44% of perp DEX volume runs through it, with more than 70% of open interest. The protocol generates a $640M annualized fee run rate, of which 97% gets used to buy back HYPE tokens on the open market every day. Industrial-scale buy-and-burn tied directly to a real, measurable business.

Aster has carved out share with a different bet: aggressive incentives, multi-chain access, and a retail-friendly interface that feels closer to Binance than to a DeFi protocol. Euphoria, an early-stage MegaETH project that raised $7.5M from over 100 investors last year, is doing for crypto derivatives what Robinhood did for stock options. Mobile-first, tap-to-trade, designed for the user who doesn’t know what a maker-taker fee is and doesn’t want to learn.

Three different bets on who the next billion derivatives users actually are. The shared thesis is that the perpetual contract is too useful to stay in a niche, and the venue that wins the user experience battle captures a real business.

How sophisticated traders use perpetuals for alpha

This is the part most retail readers underestimate. Perpetuals aren’t only a leverage tool. They’re a yield instrument for anyone who understands the funding rate.

The cleanest example is the cash-and-carry trade. Buy spot Bitcoin, short the perpetual at the same size. When funding is positive, longs are paying you to hold a delta-neutral position. You collect a yield that’s mechanical, not directional. Ethena built an entire $5B+ synthetic dollar around exactly this mechanic.

Hedge funds run more complex versions. Funding rate arbitrage across venues, basis trading between perpetuals and dated futures, and delta-neutral yield strategies that use perpetuals to hedge directional exposure on yield-bearing collateral. Most of it looks boring on paper - which is kinda the point.

The takeaway is that “yield” in crypto often turns out to be a sophisticated trader understanding the plumbing well enough to harvest mechanical spreads that exist because the market is still pricing in maturation.

The risks worth saying out loud

Three things will hurt you in perpetual markets:

• Liquidation. Leverage compounds in both directions. At 50x, a 2% adverse move wipes your position. Cascading liquidations are a feature of these markets, not a bug.

• Funding rate flips. If funding moves against you and stays there, you bleed continuously even when your directional thesis is right.

• Counterparty and oracle risk. On a centralized exchange, you carry the exchange itself (see FTX). On a DEX, you carry smart contract integrity and oracle reliability. Both are real.

Most retail traders who touch high-leverage perpetuals lose money. The instrument is brilliant. The way it’s typically used by retail is not. That distinction is worth keeping straight.

BUFFETT FRAMEWORK QUESTION

“Would I be comfortable explaining this trade to someone who has to live on what I make from it?” If the answer is no, the position is too big or the strategy is too complex.

What the next ten years might look like

Perpetuals have stopped being a crypto-only product.

Hyperliquid now offers perpetuals on oil, gold, silver, and the S&P 500. During the Iran conflict, crude oil perps cleared $1.7 billion in daily volume on a decentralized exchange that nobody at the CME would have given the time of day three years ago.

The S&P 500 perpetual cleared $100 million on its first day.

Combine perpetuals with tokenization and you get something more interesting than either alone. A perpetual on a tokenized treasury bill, a tokenized stock, an emerging-market currency, or a real-world asset that doesn’t usually trade after hours. The CME’s hours and the NYSE’s closing bell stop being binding constraints on synthetic exposure to any asset on earth.

That’s why TradFi keeps quietly investing in this space.

• JPMorgan published research on Hyperliquid’s commodity perps last quarter.

• Grayscale, Bitwise, and VanEck have all filed for spot HYPE ETFs.

• CFTC opened formal consultations on perpetual futures 24/7 derivatives trading.

None of that happens unless serious institutions believe the instrument has legs.

The perpetual futures contract was invented to solve a narrow problem for a niche group of crypto traders in 2016. Ten years later it has become one of the largest financial markets on the planet, and the design choice that made it work is starting to reshape how derivatives function across asset classes.

You don’t have to trade perpetuals to benefit from understanding them, the same way you don’t have to short stocks to understand how short selling shapes price discovery. The financial innovations that matter usually start small and look like toys until they don’t. This one stopped looking like a toy a while ago.

Happy 10th birthday to the forever contract.🥳

Matthew Snider is the founder of Block3 Strategy Group, author of “Warren Buffett in a Web3 World,” and publisher of the BitFinance newsletter. He holds a Series 65 and MBA, and has been an active participant in digital asset markets since 2015. This article is for educational purposes only and should not be considered financial advice. Always consult with a qualified professional before making investment decisions.

Sources

• BitMEX, “The Evolution of Funding Rates: 9 Years of BitMEX’s XBTUSD Funding Rate Analysis,” Q2 2025 Derivatives Report.

• DefiLlama Perp DEX Volume Rankings, Q1 2026 data.

• Datawallet, “Crypto Perpetual Futures Statistics & Trends in 2026,” April 2026.

• DL News, “Aster and Hyperliquid drive $2tn volume record as perp DEX competition heats up,” September 2025.

• Yellow.com, “Hyperliquid Hits 44% Of All Perp DEX Volume,” March 2026.

• The Block, “MegaETH-based crypto derivatives trading app Euphoria raises $7.5 million in seed funding,” August 2025.

• Galaxy Research, “The Investable Universe 2.0,” August 2025.

The question I keep coming back to is whether the layer above the chips has any investable representation outside equity markets.

Remember, this layer does the actual compute and accesses the infrastructure that AI applications need to consumeIt does. Most of it is still speculative.

One project in particular has built something I find genuinely worth understanding: Venice (VVV) and its companion token Diem (DIEM).

This article is mostly about that ecosystem. The bullish case, the risk-managed view, and why the founder behind it matters. At the end, I’ll give you a quick snapshot of 3 other AI projects I’m watching in the crypto space, but the depth is on Venice.

Buffett Framework Question

“What does this business actually do, and does it have to keep doing it for the token to be worth holding?” For AI infrastructure projects, the answer has to involve real compute being produced or consumed, not just narrative momentum.

Usual disclaimers apply:
✅ Educational only. ✅ Not investment advice. ✅ Do your own research.

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Start With the Founder

Before getting into the mechanics, it’s worth understanding who built Venice. Erik Voorhees has been operating in crypto since 2011, which makes him one of the longest-tenured builders in the entire space. He was involved with BitInstant in the early Bitcoin days. He founded SatoshiDice in 2012 and later settled with the SEC over what became one of the first widely-discussed token offering cases. In 2014, he founded ShapeShift, the non-custodial exchange that he ran through multiple cycles and eventually decentralized.

Two things matter about his track record for the Venice thesis.

1. The first is ideological consistency. Voorhees has been a vocal advocate for financial sovereignty, privacy, and censorship resistance for the better part of 15 years. Venice is the logical extension of that worldview applied to AI. A privacy-first platform that runs uncensored open-source models is exactly what you’d expect him to build if he believed AI was about to become as important to society as money. He believes that, and he’s building accordingly.

2. The second is operational durability. Most crypto founders haven’t survived more than one cycle. Voorhees has shipped through at least four. He has experience navigating regulators, running production infrastructure, and managing a token economy in real conditions. That’s a rare profile in this space, where most projects are run by anonymous developers or first-time founders with academic backgrounds. None of that guarantees Venice succeeds, but it raises the floor of seriousness considerably.

   ---

Venice (VVV): The Access Layer

By the numbers

• VVV market cap ~$700-800M (May 2026)

• ~46M circulating of 80M total supply

• ~42% of original supply already burned

• Annual emissions cut 25% in Feb 2026 (8M to 6M VVV)

• 1.3M+ users, 8.8M monthly visits, 15,000+ inference requests/hour

• Founded by Erik Voorhees (ShapeShift), built on Base

Venice is a privacy-first AI platform. It gives you access to leading open-source models like Llama and DeepSeek without storing your data, logging your prompts, or filtering your outputs. The platform itself is the consumer product and the investable layer sits underneath.

Most AI APIs charge per request. Predictable for casual users, painful for serious builders, because costs swing with usage and budgeting gets hard.

Venice does it differently. You stake VVV tokens and receive a proportional share of the network’s total inference capacity. Stake 1% of all staked VVV, get 1% of Venice’s daily compute. Forever. You don’t spend the tokens. You lock them, use the compute, and earn staking yield on top, currently running 14 to 18% depending on utilization. The tokens stay yours and the compute keeps flowing.

Oh, and yeah, the token has done almost a 10x

While this alone is interesting, what makes the ecosystem worth a longer look is DIEM.

DIEM: The Financial Primitive

DIEM is the companion token Venice introduced in 2025. Each DIEM represents $1 per day in API credit, in perpetuity. You mint DIEM by locking staked VVV. Once minted, that DIEM produces compute access forever, regardless of what VVV does in the open market.

Think of it like a power purchase agreement. A factory locks in 10 years of electricity at a fixed rate so a price spike can’t kill the business. DIEM applies the same logic to AI inference. You’re not flipping a token. You’re buying production capacity at a known cost, indefinitely.

For an autonomous agent that needs predictable unit economics to operate as a business, that kind of certainty is the difference between a working product and a science experiment.

The bigger picture is what this could mean for the AI buildout. Compute prices have come down dramatically over the past two years, but demand keeps rising faster than supply. Any serious AI builder has to budget for inference costs that could swing 50% in either direction over a 12-month window.

DIEM is one of the first credible attempts to turn that operational expense into a fixed asset on a balance sheet. Whether that primitive scales is the open question. Whether it’s the right idea for this moment seems much less debatable.

How Venice Makes Money (and Why It Matters for Token Holders)

Two flywheels drive the economics, both tied to actual platform revenue.

The first is the buy-and-burn. A portion of subscription revenue automatically buys VVV on the open market and burns it. Each Pro signup burns $2 worth of VVV. Pro+ burns $5. Max burns $10. These aren’t governance promises. They’re automated mechanisms tied directly to user growth. The more the platform grows, the more tokens get removed from circulation, permanently.

The second is supply discipline. Annual emissions were cut from 8M to 6M VVV in February. Roughly 42% of the original 100M supply has already been burned, including a one-time burn of unclaimed airdrop tokens. The supply curve is moving aggressively in the right direction, which is unusual in crypto where teams typically prioritize their own emissions over holder dilution.

Demand comes from a different direction. AI agents, developers, and individual users stake VVV to access inference at zero marginal cost. As the platform expands its GPU fleet, the same staked VVV represents a larger share of a bigger pie. Token holders benefit from deflationary mechanics on one side and growing capacity on the other. That’s a coherent value-accrual story, which is more than I can say for most tokens in this category.

Buffett Framework Question

“Would I rent or own this resource?” The DIEM thesis is that AI compute is becoming infrastructure important enough that locking it in at a fixed cost makes sense. That’s the same logic that drove fuel hedging, power purchase agreements, and 30-year mortgages. The bet is whether AI inference rises to that level of strategic importance for enough buyers.

The Bullish Case

Put together, the bull case for VVV and DIEM is one of the cleaner ones in crypto right now.

Venice is a working business with revenue. 1.3 million users, 8.8 million monthly site visits (up 15% over a three-month window), and 15,000+ inference requests per hour. The buy-and-burn engine is tied directly to that revenue. As the platform grows, the token gets scarcer in a way that’s visible and verifiable on chain.

DIEM creates a financial primitive that didn’t exist before. Locking in AI compute at a fixed cost matters more as AI becomes critical infrastructure, not less. If autonomous agents become a meaningful share of internet activity over the next five years (which is what almost every major AI lab is now publicly betting on), the demand for predictable inference capacity grows alongside them.

The founder has shipped through four cycles. Voorhees doesn’t pivot, doesn’t disappear, and doesn’t run sketchy promotions. His worldview maps cleanly to where AI is heading, which means his execution priorities are likely to stay aligned with the project’s stated mission rather than drifting toward easier revenue.

The tokenomics favor long-term holders. Aggressive burns, transparent emission cuts, no governance theater. The team has made decisions that hurt their own emissions allocation to benefit stakers. That’s rare.

The Risk-Managed View

Now the other side of the ledger. Anyone who only reads the bull case isn’t doing real work.

Governance is centralized (and that’s OK!). The emission cuts, the burn parameters, and the DIEM launch were all decisions made by the Venice team without token-holder voting. Efficient for moving fast, fragile if the team ever pivots. A protocol built on decentralization principles that runs on centralized governance has a contradiction baked in. That contradiction is fine right now but - as we’ve seen in crypto - it might not be later.

The product is concentrated. Venice is one platform offering one core service. If a major competitor (OpenAI, Anthropic, Google) offers similar privacy guarantees at lower cost, the case erodes quickly. The platform has to keep winning users against deep-pocketed incumbents that are themselves rolling out privacy features. The moat depends on staying meaningfully ahead on privacy and uncensored access, which is a moving target.

Valuation is rich. VVV is up over 1,500% from its December 2025 low and trades at roughly $700 to $800 million market cap. Some of the move is fundamental. Much of it is reflexive momentum tied to the broader AI rally. A 50% correction from here would still leave the token well above its December trough, but it would be painful for anyone buying at recent highs.

Regulatory exposure is real. Privacy-first AI that processes uncensored outputs sits in genuinely uncharted territory. If U.S. or European regulators decide decentralized AI platforms need to implement content moderation or KYC requirements for high-volume users, the entire value proposition shifts. Voorhees has navigated regulators before, but the AI regulatory environment is going to look very different from anything he’s dealt with in financial services.

Position sizing matters. I hold a small VVV position, representing roughly 7-8% of my overall digital asset portfolio, with a cost basis under $9. That weighting reflects high conviction in the thesis combined with healthy caution about a token that has run hard in a short window. I’d be careful about anyone treating a token up 1,500% in five months as a high-conviction buy at current levels. The thesis is intact. The entry matters.

3 Other AI Plays I’m Watching

Venice and DIEM are the deep dive. Here are three others I’m tracking at a higher level, with the headline numbers and the single reason each is worth your attention.

Bittensor (TAO): The production layer for decentralized AI

• Market cap: ~$3-3.5B (top 30)

• Supply: ~10.9M circulating, 21M hard cap

• Active subnets: 128 (expanding to 256)

• Q1 2026 compute revenue: ~$43M across subnets

• Institutional inflows: NVIDIA ~$420M, Polychain ~$200M

Why I’m watching: Bitcoin-style scarcity (21M cap, halving cut daily emissions in half) combined with the first credible proof that decentralized training can compete with centralized AI.

Key risk: Governance friction. Covenant AI publicly left in April 2026 and dumped 37K TAO on the way out.

NEAR Protocol (NEAR): The AI-native Layer 1 bet

• Type: Base-layer blockchain positioned as “the chain for AI”

• Co-founder: Illia Polosukhin

• Polosukhin’s pedigree: One of eight authors of the 2017 transformer paper

• Thesis: AI agents will be the primary users of blockchain

• Key product: NEAR Intents (cross-chain agent settlement)

Why I’m watching: Polosukhin’s transformer research underpins GPT, Claude, and the entire current AI boom. NEAR is the only L1 with that kind of pedigree at the founder level.

Key risk: Competing with Ethereum, Solana, and Base for the same agentic positioning. Layer 1 narratives are crowded.

Quick Note: Legend wrote an awesome article comparing Near and TAO that I would highly recommend you read.

Virtuals Protocol (VIRTUAL): The agent payment and tokenization layer

• Market cap: ~$485M

• From ATH: Down 86% from $5.05

• Supply: ~656M of 1B (no future inflation)

• Chain: Base

• Key standard: ERC-8183 (co-authored with Ethereum Foundation)

Why I’m watching: Coinbase’s x402 Foundation launch at Consensus 2026 (with Visa, Mastercard, Stripe, AWS, Google) validates the agentic commerce thesis. Virtuals has been building this infrastructure for two years.

Key risk: Agent narrative has cooled hard. Most agent tokens on the platform haven’t found durable use cases.

Putting It Together

The AI buildout needs production, access, and payment rails. Bittensor sits at production. Venice and DIEM sit at access. Virtuals sits at agent payments. NEAR is making a bet on being the settlement layer underneath all of it. None of these are mutually exclusive, and a serious AI agent five years from now might use all four.

Of the four, Venice is the one I find most worth understanding right now. DIEM converts a recurring expense into a fixed asset in a way that’s actually useful. The supply mechanics are aggressive, the platform is shipping, and the founder has shipped before. That combination is hard to find in crypto.

For most retail investors, NVIDIA, AMD, or an AI ETF probably remains the cleaner way to express the AI thesis. These crypto tokens are higher beta and require more work to understand.

I push back on the assumption that the only way to invest in AI is to buy the obvious names. The plumbing layer is being built, and some of it lives on chain. Whether you participate is a separate question from whether you should understand it.

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Matthew Snider is the founder of Block3 Strategy Group, author of “Warren Buffett in a Web3 World,” and publisher of the BitFinance newsletter. He holds a Series 65 and MBA, and has been an active participant in digital asset markets since 2015. This article is for educational purposes only and should not be considered financial advice. Always consult with a qualified professional before making investment decisions.

Both things are true. Sentiment was tepid, the deals were enormous, and the themes that mattered were specific. Here are five worth your time.

1. Agentic banking stopped being a thought experiment

Anchorage Digital’s Nathan McCauley used the mainstage to launch what he’s calling an agent bank. The pitch is that we’re heading into a trillion-dollar industry where agents pay each other, agents pay merchants, and agents get paid.

Then Coinbase introduced the x402 Foundation, now governed by the Linux Foundation as of April, with Adyen, AWS, American Express, Circle, Cloudflare, Fiserv, Google, Mastercard, Microsoft, Polygon, Shopify, Stripe, Solana, and Visa as inaugural members. The name comes from RFC 7231, section 6.5.2: HTTP status code 402, “Payment Required,” which the IETF reserved in 2014 “for future use.” That future arrived this week.

The numbers behind the launch are truly impressive and intriguing.

x402 had already processed over 50 million transactions before the foundation announcement, and stablecoin volumes on the related rails now exceed $11 billion in circulation with 200 million-plus transactions per month.

AWS chose this week to launch Amazon Bedrock AgentCore Payments in preview, with native x402 support. Galaxy Research estimates agentic commerce could represent $3 to $5 trillion in B2C revenue by 2030.

The opportunity for allocators is the layer underneath that figure: API micropayments, compute provisioning, and machine-to-machine settlement, the boring rails the agents need to function. If you’re advising clients on the AI buildout, the payments infrastructure is no longer hypothetical. It’s being assembled by the same firms that already process most of the world’s transaction volume.

2. Tokenization quietly turned into M&A

Bullish announced it’s acquiring Equiniti for $4.2B.

Equiniti is the system of record for nearly 3,000 issuer clients, processes around $500 billion in annual payments, and serves over 20 million verified shareholders.

Their issuer roster includes Berkshire Hathaway, Rolls-Royce, and Moody’s. Pro forma, the combined company expects roughly $1.3 billion in adjusted revenue and over $500 million in adjusted EBITDA less Capex in 2026, with 20% projected revenue growth from tokenization through 2029. BLSH shares climbed 17% in morning trading. Clear Street kept a Buy with a $50 target, calling it the gap-filler in Bullish’s tokenization thesis.

The framing held up across the conference. Stablecoins (now $300 billion in market cap and roughly $10 trillion in annual payments volume) and digital commodities have already migrated onchain.

Global securities are a $270 trillion-plus market, and the institutional players have moved past pitching the idea and started buying the plumbing. Securitize and Computershare are now publicly working to bring parts of the $70 trillion U.S. equities market onchain, which means the Bullish deal looks less like an outlier and more like the first large move in what will be a quieter wave of consolidation.

Crypto M&A in 2025 already hit roughly 260 deals totaling $8.6 billion, about four times the prior year, per Pitchbook data, and the Bullish-Equiniti transaction by itself is half that 2025 total.

3. The chain conversation converged onto Canton

Nearly every chain conversation I had ended up at one way or another falling to Canton Network.

Partners building on it, institutions evaluating it, very little chatter about the alternatives. If you’ve been holding a strict “permissionless will win” thesis, this conference was a counterargument worth taking seriously.

It doesn’t mean Canton wins, but it does mean the institutional buyer is more comfortable with a permissioned chain than the crypto-native investor expects them to be. Canton’s pitch leans on a privacy-first architecture and the Daml smart contract language, which is roughly what every regulated counterparty I spoke to said they needed from a settlement layer before they’d even take a meeting.

For allocators with broad public market exposure, the real question is which infrastructure stack each tokenization corridor settles on, and whether your existing custody and prime relationships are positioned to ride those rails when they go live.

4. Tradfi is no longer benchmarking against Tradfi

The most repeated competitive frame I heard from traditional brokerages: their direct competitors are Coinbase, Kraken, and Robinhood, not each other.

The “Old Money, New Assets” panel with Morgan Stanley’s Jed Finn and Zerohash’s Edward Woodford was the cleanest version of the argument. The wealth management seat at the table now includes someone whose product roadmap looks a lot like a crypto exchange.

Mastercard and Visa illustrated the same dynamic from the issuer side, with Mastercard focused on B2B payments expansion and Visa on agentic commerce. For RIAs, the platforms your clients use are converging, and the advisor who can speak both languages is going to look very different five years from now than the advisor who picked one side.

5. The mood was bearish in a way the headlines hid

Coinbase laid off 14% of its workforce the same morning a16z announced its $2.2B Crypto Fund 5. Crypto VC funding hit $662M in April 2026, its lowest point since May 2025 and down 74% year over year. Most former crypto VCs now describe themselves as crypto and AI VCs. Several funds I talked to are raising but not deploying.

Yet a16z and Haun Ventures pulled in $3.2 billion combined in a single week, and both centered the same three themes: stablecoins, tokenization, and the agentic economy. a16z’s new fund is half the size of its 2022 vehicle, which tells you these firms are sizing for discipline rather than froth. The signal is concentration, not retreat. Capital is being repositioned for the next cycle, and the people repositioning it aren’t broadcasting the moves yet. Per several policy folks I spoke with, the Clarity Act could pass as early as end of May, which would change the calculus for a lot of the dry powder currently waiting on the sideline. Looking forward to next year.

Final Consensus: If you only read the headlines, you got one story. If you spent the week on the floor, you got a different one. Both are real. Holding both in your head is the work.

🛑 REMINDER 🛑

Quick reminder of what we’re building. Live indicators. The research behind them. The methodology taught alongside the signal. A small room where you leave knowing how the work actually gets done

I’m building the early cohort for when the Discord opens and the first indicators ship. If you want a seat, this is where to claim one.

Interested? Fill out the 30-second interest form here. 👈

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This Week In 2 Mins

Buffett Just Compared Markets to a Church with a Casino Attached (May 5)

At Saturday’s Berkshire meeting, Buffett described markets as a church with a casino attached, and noted the casino has gotten very attractive. Monday morning gave us both halves on the same news cycle.

• GameStop’s $11B market cap made an unsolicited $55B hostile bid for eBay with no answer for the math (casino).

• DTCC quietly confirmed July production timelines to tokenize a slice of its $114 trillion in real-world assets under custody, with 50 firms in the group (church).

Burry exited GameStop within 48 hours when the data changed. The casino had every camera in the building. The church had a press release.

Read the full article here.

Five Layers Down: The Investable Stack Behind the Steroid Olympics (May 8)

Enhanced Games (the Steroid Olympics) prices its IPO on Friday at a $1.2B valuation. Three sports, four days at Resorts World Las Vegas, with athletes openly using FDA-approved performance enhancers under medical supervision.

• The Games themselves are the marketing engine.

• The real investment thesis is the consumer health stack underneath: TRT, peptides, GLP-1 derivatives, longitudinal diagnostics.

The longevity market is projected to grow from $65B in 2023 to $314B by 2030 at a 25% CAGR, with or without the swim meet. Five layers worth tracking, from the SPAC itself down to prediction markets like Kalshi.

The Games are the ad campaign. The portfolio sits one or two layers below.

Read the full article here.

Winners🏆

• Bullish (BLSH) - (who now owns CoinDesk & Consensus). Shares climbed 17% in morning trading on the Equiniti announcement. Clear Street kept a Buy rating with a $50 price target, calling the deal the gap-filler in the firm’s tokenization thesis.

  

• Berkshire Hathaway shareholders. Equiniti is BRK’s transfer agent, which means Buffett’s 4 million-plus shareholders are about to be among the first to sit on tokenization-ready issuer infrastructure, whether or not BRK ever opts in.

• Stablecoin issuers and infrastructure. All three of the largest VC announcements of the week (a16z’s $2.2B, Haun’s $1B, and the Bullish deal) centered stablecoin rails as the durable adoption signal. Annual payments volume is now $10 trillion.

  ---

Losers📉

• Coinbase headcount. The 14% reduction in force landed mid-conference and reset the mood across the floor. The release came the same morning the firm’s biggest VC backer announced a fresh $2.2B fund.

  

• Strategy (MSTR). Q1 earnings missed EPS expectations even as the firm continued aggressive bitcoin accumulation, including a 34,164 BTC purchase in April for $2.54 billion. Shares dipped after-hours.

• DeFi total value locked. TVL fell from a monthly high of $99.5B to $84.3B in April after exploits at KelpDAO and Drift, a 15% drawdown that’s worth tracking against the broader risk-on narrative.

  ---

Watch this week (May 11 to 15)

• Tuesday: April CPI. Headline expected at 0.6% MoM and 3.7% YoY, with core at 0.3% MoM and 2.7% YoY. The print lands while a new Fed chair confirmation works through the Senate. Watch the rate path repricing.

• Bullish (BLSH) Q1 print. First read on tokenization revenue mix since the Equiniti announcement. The sustainable revenue question is the real test of whether the thesis holds beyond crypto trading volumes.

• Clarity Act floor vote watch. Policy contacts I spoke with at Consensus believe end-of-May is realistic. A passage signal would re-rate everything in the digital asset compliance stack.

• AWS AgentCore Payments adoption. With AWS launching native x402 support on May 7, watch which large enterprises announce pilots first. Early adoption will tell you whether agentic commerce is a 2027 story or a 2026 one.

  ---

🛑 REMINDER 🛑

Quick reminder of what we’re building. Live indicators. The research behind them. The methodology taught alongside the signal. A small room where you leave knowing how the work actually gets done

I’m building the early cohort for when the Discord opens and the first indicators ship. If you want a seat, this is where to claim one.

Interested? Fill out the 30-second interest form here. 👈

Interest Form

Matthew Snider is the founder of Block3 Strategy Group, author of “Warren Buffett in a Web3 World,” and publisher of the BitFinance newsletter. He holds a Series 65 and MBA, and has been an active participant in digital asset markets since 2015. This article is for educational purposes only and should not be considered financial advice. Always consult with a qualified professional before making investment decisions.

Yesterday morning while at Consensus in Miami, Squawk Box explained it. That structure is the venue for Enhanced Games, which prices its IPO today and stages its inaugural event over Memorial Day weekend.

My mom called this thirty years ago. Watching the steroid era of baseball unfold, she’d say something close to:

“I want to see them swing a bat with their head the size of a watermelon and arms the size of redwoods.” Half-joking, mostly correct.

The Games are interesting on their own. The investment thesis underneath them is more interesting still.

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Quick Primer For Newcomers (like me!)

The Enhanced Games is a new sports property launched by Australian entrepreneur Aron D’Souza in 2023.

Three sports across four days at Resorts World Las Vegas: swimming, track and field, weightlifting.

• 40 athletes

• $25 million in total comp

• $1 million bounties for breaking world records (100m sprint & 50m freestyle)

The catch is that athletes are encouraged, rather than banned, from using performance-enhancing drugs.

Only FDA-approved substances prescribed by licensed U.S. physicians are allowed. Pre-competition medical screening includes blood panels, EKGs, and cardiac MRIs. WADA, USADA, the IOC, and World Aquatics have all condemned the event, with World Aquatics banning any participant from its competitions going forward.

The cap table reads like a who’s-who of contrarian capital.

• Peter Thiel led the seed alongside Christian Angermayer, who runs longevity, biotech, and psilocybin investments through his family office Apeiron, and Balaji Srinivasan.

• The Series B was co-led by Donald Trump Jr.’s 1789 Capital, with the Winklevoss twins and Saudi prince Khaled bin Alwaleed Al Saud also in the round.

• The SPAC merger with A Paradise Acquisition Corp values Enhanced at a $1.2 billion enterprise value with up to $200 million in fresh capital.

That’s the headline story. Here’s what you’ll need to understand for portfolio purposes.

The Olympics format is the marketing engine

Enhanced launched a direct-to-consumer business in early 2026 selling testosterone replacement medicines and other consumer health products. The CEO has been straightforward about the model. The Games “showcase that performance enhancements, under the right clinical and medical supervision, can deliver long term health and longevity benefits.”

The competition is an ad campaign for a consumer health business.
That’s the reframe.

Think Red Bull.

Most people associate the brand with energy drinks. The Formula 1 team, the cliff-diving series, and the wingsuit jumps from the stratosphere are the marketing layer.

The drink is the product. Enhanced is running the same playbook for performance medicine, with one important difference: the consumer health category they’re feeding is enormous and growing fast.

The global testosterone replacement therapy (TRT) market sits around $2 billion today, growing at roughly 4.6% annually. The broader longevity category, which captures peptides, GLP-1 derivatives, hormone optimization, and adjacent biomarkers, is projected to expand from $65 billion in 2023 to $314 billion by 2030 at a 25% CAGR.

Enhanced is positioning into the bigger number, riding demographics and disposable income rather than the slower clinical TRT trajectory.

That’s where the investment stack starts to take shape.

What Enhancement Actually Delivers

Kristian Gkolomeev’s 50m freestyle progression. Source: The Sports Examiner, Enhanced Games announcement event (May 2025).

Worth grounding the conversation in real data. Kristian Gkolomeev’s personal best across his Olympic career was 21.44 seconds in the 50m freestyle. After two weeks of openly disclosed PEDs and using a current-legal swimsuit, he hit 21.03. In a now-banned super suit, 20.89 seconds, technically faster than Cesar Cielo’s 2009 world record of 20.91. That’s a 1.9% improvement over a peak Olympic time, achieved on a compressed prep cycle.

The performance gain looks small, but the economic implications scale far beyond it. A 1.9% performance edge marketed inside a $314 billion consumer health category is worth a lot of public market valuation.

The 5-Layer Stack

• Layer 1: The direct play. A Paradise Acquisition Corp is the SPAC vehicle. Enhanced closed a $40 million PIPE that converts into public shares once trading begins. The risk profile is venture-equity-in-a-public-wrapper. Significant upside if the format catches on, total loss potential if the first event flops or a medical incident derails the broadcast. Treat this as speculative exposure rather than core position material.

• Layer 2: The TRT and peptide supply chain. This is where the patient capital lives. Hims & Hers (HIMS) is already pivoting hard into this exact category, investing in a California peptide manufacturing facility and planning a 2026 longevity specialty covering peptides, coenzymes, and GLP/GIP treatments. The company is launching testosterone replacement therapy this year through an exclusive partnership with Marius Pharma for oral testosterone. Its 2.5 million subscriber base is the moat Enhanced has to compete against rather than the one Enhanced builds. Eli Lilly (LLY) sits one rung up the supply chain with GLP-1 dominance and the LillyDirect distribution layer that now routes Zepbound prescriptions through Hims. AbbVie (ABBV) carries the legacy AndroGel franchise, which is generic-pressured but still cash flow generative.

• Layer 3: Diagnostics and monitoring. Medical supervision is the regulatory choke point that makes the whole model work. Every athlete gets blood panels, EKGs, cardiac MRIs. Every consumer customer ordering testosterone or peptides through a telehealth platform needs the same baseline. Tempus AI (TEM) sits at the genomic testing layer and was already on the radar from my AI value chain piece in March. Quest Diagnostics (DGX) and LabCorp (LH) handle the volume blood work. The wearable layer, including Apple, Garmin, plus private names like Oura and WHOOP, provides continuous biomarker data that turns a one-time prescription into a longitudinal subscription.

• Layer 4: The Vegas experience economy. Resorts World is owned by Genting Berhad, a Malaysian conglomerate that doesn’t trade on U.S. exchanges. The cleaner U.S. expressions of Vegas-as-spectacle are MGM Resorts (MGM), Caesars (CZR), and Wynn (WYNN). Live Nation (LYV) deserves a mention because the Enhanced closing event includes a Killers concert and an afterparty at Zouk. This thread connects to the Tropicana piece I wrote earlier this year about Vegas pivoting from gambling-first to spectacle-first hospitality. Enhanced is the latest data point.

• Layer 5: Downstream betting infrastructure. If enhanced records become a persistent product category, regulated betting markets pick up a new vertical. DraftKings (DKNG) and Flutter (FLUT) are the obvious U.S. names. Prediction markets like Kalshi are the more interesting expression because they don’t need state-by-state sports betting licensure to operate, and recent regulatory tailwinds have widened their lane meaningfully.

The Risk Worth Flagging

The first event could go badly. Like…really bad.

A medical incident on the broadcast would change the regulatory conversation overnight, which is exactly why the FDA-approved-only and pre-competition screening framing exists. Insurance is doing real work in this business model. World Aquatics has already banned participants from its future competitions, which limits the talent pool to retired or near-retirement athletes. The format hasn’t been proven yet.

The TRT and peptide thesis stands on its own without Enhanced Games. Hims is launching this category whether or not the swim meet draws an audience. Lilly is building distribution rails regardless. The longevity market is forecast to compound at 25% per year through 2030 because of demographics and disposable income, not because of a Memorial Day weekend exhibition. Enhanced is the loudest signal yet that the category is real, but the category was already real.

How I’m Allocating. What I’m Watching

Do I buy this stock on Friday? Absolutely not. Friday’s pricing is the immediate event. Worth tracking opening-day flows but not chasing.

Am I interested in the space? Hell yes!

Honestly, I’m so very curious to see how this narrative gets priced. If we are able to collect valuable data on the use of PEDs, it could continue to enhance the way we engage with the complex idea known as “longevity”.

I also own - as we’ve discussed before - Tempus AI so I already have some tangential exposure which makes me feel like I have some proverbial skin in the Enhanced Games.

The more meaningful signal will come on May 24th, the morning after the inaugural games. If world records fall and the event runs cleanly, expect the consumer health side of the cap table to re-rate within weeks. If something goes wrong, the conversation flips to regulation overnight.

Either way, the five-layer stack is where the durable thesis lives. The Games are the ad campaign, but the portfolio sits one or two layers below.

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🛑 REMINDER 🛑

Quick reminder of what we’re building. Live indicators. The research behind them. The methodology taught alongside the signal. A small room where you leave knowing how the work actually gets done

I’m building the early cohort for when the Discord opens and the first indicators ship. If you want a seat, this is where to claim one.

Interested? Fill out the 30-second interest form here. 👈

Interest Form

Matthew Snider is the founder of Block3 Strategy Group, author of “Warren Buffett in a Web3 World,” and publisher of the BitFinance newsletter. He holds a Series 65 and MBA, and has been an active participant in digital asset markets since 2015. This article is for educational purposes only and should not be considered financial advice. Always consult with a qualified professional before making investment decisions.

Seriously.

Reuters counted roughly 12,000 of the 18,000 seats occupied, down from the 40,000-plus that Buffett used to draw. See’s Candies had hundreds of unsold boxes of Berkshire-branded chocolates by the time the registers closed Saturday evening. Dairy Queen had leftover ice cream bars. Fechheimer had a rack of Andy Warhol-style Buffett-and-Abel T-shirts that nobody bought.

The whole weekend had this gentle, transitional quality to it.

• Greg Abel as a Squishmallow.

• Greg Abel on the windshield of a Pilot semitruck, in the driver’s seat now.

• A See’s Candies commemorative tin with Abel playing hockey while Warren and Mrs. See watched in matching gear.

You could feel the franchise trying very hard to make the new guy stick, and you could also feel that nobody outside the value-investing diehards quite knows who Greg Abel is yet. He’s good. He’s smart. He’s been at Berkshire for 25 years.

He’s also not Warren Buffett, and you can’t merch your way around that.

The actual show, though, was excellent. Buffett did a 25-minute interview with Becky Quick during the lunch break that I’d recommend to anyone.

The line that’s been echoing in my head all weekend was this one:

He compared markets to a church with a casino attached, and said that while there are still more people in the church than the casino, the casino has gotten very attractive.

Then he added, plainly:

“We’ve never had people in a more gambling mood than now.”

Warren Buffett, Berkshire Hathaway Annual Meeting, May 2, 2026

Saturday afternoon, that was a rhetorical flourish from a 95-year-old at a quieter-than-usual annual meeting.

Monday morning, it was the entire market.

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The Casino Opens Early

GameStop CEO Ryan Cohen went on Squawk Box at the open with an unsolicited, hostile, $55.5 billion offer for eBay. Half cash, half stock, a $20 billion financing letter from TD, and no prior conversation with eBay’s board. GameStop’s market cap on Monday morning sat around $11 billion. The offer is roughly five times the size of the acquirer.

Andrew Ross Sorkin asked the obvious question, which is how the math works. Cohen’s answer should be required viewing for anyone who still thinks the meme stock era is over. He said the deal is half cash, half stock, that there’s a $20 billion financing letter from TD, that the company has the ability to issue stock to get the deal done. When pressed for any further detail, his actual answer was: “the details are on our website.”

I’d embed the full clip here if email allowed me to, and you should watch it on Substack where I can. I’m not exaggerating when I say it’s one of the craziest CEO interviews I’ve seen on CNBC in years. Top five, easy. Cohen looked annoyed that anyone was asking him to explain how a company worth eleven billion dollars plans to buy one worth fifty-five.

(the first 2 mins are DEFINITELY worth a watch)👇🏻

Here’s the structural problem.

If you split the offer in half, that’s roughly $27.75 billion in cash and $27.75 billion in stock. The TD financing letter covers $20 billion of the cash, which leaves about $8 billion still to find. The stock half is the bigger issue.

Issuing $27.75 billion of GameStop equity against an $11 billion market cap is a roughly 2.5x dilution event before you even get to the missing cash.

Add the gap in financing and you’re looking at something closer to a 3x to 4x dilution to clear the deal. Cohen’s hand-wave about the combined company being “more efficient” doesn’t fix that. There’s no version of this transaction where existing GameStop shareholders are not catastrophically diluted.

GameStop traded down roughly 10 percent on the news. EBay traded up around 6 percent. The market did the math even if Cohen wouldn’t.

Burry Walks Out

The most interesting part of the story isn’t Cohen, it’s Michael Burry.

Burry took a position in GameStop in January, after years of skepticism, on the bet that Cohen was finally serious about turning the company into a real cash-flow business.

On Monday, he posted to Substack that he wouldn’t be holding the position past the week.

By the afternoon, the Wall Street Journal reported he’d already exited entirely. His public reasoning was simple: he supports Cohen’s vision, but the price is too high and there are better targets if you genuinely want to compete with Amazon.

Burry isn’t a meme trader.

He’s a value investor who briefly tried to underwrite a thesis that Cohen had become a value-creating capital allocator.

The eBay bid invalidated that thesis in a single weekend. When the data changes, the value investor leaves the position. That’s the whole job.

If you’re building a Buffett-style framework for evaluating management, the lesson here writes itself. You can be patient with a CEO who is patient with capital. You cannot be patient with a CEO who tries to use his stock as currency to acquire a business five times his size and then refuses to walk through the math on television. Those are two different people, and Burry recognized which one he was actually invested in.

The Church Opens Quietly

While Cohen was on CNBC and Burry was drafting his exit note, the Depository Trust & Clearing Corporation put out the dullest press release of the day.

DTCC announced that it has now convened more than 50 financial firms in a working group to deliver its tokenization service, with limited production trades targeted for July 2026 and a full launch in October. The service will tokenize Russell 1000 constituents, ETFs tracking major indices, and U.S. Treasury bills, bonds, and notes. It runs on top of the No-Action Letter the SEC granted DTC in December 2025, which authorized the program for three years.

DTC currently custodies real-world assets valued at over $114 trillion.

I want you to sit with that number for a moment.

One hundred fourteen trillion dollars.
$114,000,000,000,000

The post-trade utility that clears and settles essentially every U.S. equity, bond, and Treasury you’ve ever owned has just confirmed timelines to put a meaningful slice of that on-chain inside the next six months, with the largest custodians, asset managers, and brokers in the industry as design partners.

There was no CNBC interview, no CEO standoff, no meme. Just a press release that quietly said the rails are getting rebuilt, the regulators have signed off, and the launch is on a calendar.

This is what the church looks like when it’s actually working. It’s genuinely, profoundly boring, and the boredom is the point.

What the Two Stories Tell Us

If you stack the two announcements next to each other, you get a clean picture of where capital is moving and where attention is moving, and the gap between the two has rarely been wider.

The casino had every camera in the building on Monday. Cohen, Burry, the financing letter, the awkward dodges, the meme stock energy that never fully went away. There’s a reason the GameStop story will get fifty times the social media engagement that DTCC will. Drama travels faster than plumbing.

The church had 50 firms, $114 trillion in custody, a regulatory pathway, and a launch date. No drama at all. You will not see Brian Steele or Nadine Chakar trending on X this week.

A few honest observations about how I’m thinking about portfolio construction in light of all this.

• First, the structural incentive in retail markets right now is to be loud. Cohen knows that an eleven-billion-dollar company doesn’t get to bid on a fifty-five-billion-dollar company without a Squawk Box appearance to manufacture the social proof. The casino rewards spectacle. None of that changes the underlying math.

• Second, the structural incentive in institutional markets is the opposite. DTCC doesn’t need anyone’s attention. They need the No-Action Letter, the working group, and the operational readiness checklist. The church rewards process. The fact that retail rarely notices a $114 trillion plumbing upgrade is a feature of how serious infrastructure gets built, not a bug in the announcement.

• Third, Burry’s exit is the single best case study I’ve seen in months for what it actually looks like to be a disciplined value investor in a casino-heavy market. He took the swing. He got new information. He left. No regret, no defense of the original thesis, no waiting around for sunk-cost validation. That’s the discipline. It isn’t flashy, but it also isn’t optional.

Buffett’s line on Saturday wasn’t a complaint but a description. The casino is genuinely attractive right now. People are genuinely in a more gambling mood than they’ve ever been.

The job, if you take Buffett seriously, isn’t to pretend the casino doesn’t exist, but to know which side of the building you’re standing on and to be honest with yourself about why.

I’m watching the church side this week.

🛑 REMINDER 🛑

Quick reminder of what we’re building. Live indicators. The research behind them. The methodology taught alongside the signal. A small room where you leave knowing how the work actually gets done

I’m building the early cohort for when the Discord opens and the first indicators ship. If you want a seat, this is where to claim one.

Interested? Fill out the 30-second interest form here. 👈

Interest Form

Matthew Snider is the founder of Block3 Strategy Group, author of “Warren Buffett in a Web3 World,” and publisher of the BitFinance newsletter. He holds a Series 65 and MBA, and has been an active participant in digital asset markets since 2015. This article is for educational purposes only and should not be considered financial advice. Always consult with a qualified professional before making investment decisions.

BitFinance has shifted in the past few months from written contributions to driving tangible value for readers and traders. The work has gone into systems, methodology, and tools we can put in the hands of the community, with the same kind of discipline you’d find inside a real institutional desk. Today’s the right moment to surface it.

The problem we’re solving for

Retail traders, whether they’re working in equities, digital assets, or futures, are operating on thinner edges than they were ten years ago. Markets are more competitive as information advantages shrink, and execution speed catches up across most platforms. What used to be the dividing line between a good independent trader and an institutional desk has narrowed to a single thing, which is access to research that’s been done with rigor.

That kind of access still tends to live in places most retail traders can’t reach, and the asymmetry is the thing we’re trying to close.

The retail tools market hasn’t kept up with that reality.

Most paid indicator products report a Sharpe ratio without telling you how many parameter combinations were tested before settling on the one that looked best. Most published win rates come from a single market regime.

(e.g. don’t be like this…👇🏻)

Most “where this works” stories don’t include a “where this fails” page. None of those omissions are accidents, since the marketing economics of the space depend on them. The work we’re doing assumes the opposite economics.

How we’re solving it

We’ve spent the past few months building the four pieces of an alternative that lives outside the institutional walls but operates inside the institutional standard. We own all four of them, which matters more than it sounds.

The methodology is the foundation, and it’s the piece carrying the most weight.

It’s distilled from roughly 1,400 pages of quantitative literature into a process that describes what we build, what we validate, what we kill, and what we publish. The architecture is two-tiered.

• The Eight-Gate Framework is what every fund-deployable strategy has to clear before it sees client capital.

• The Retail Validation Standard is the scoped version we apply to indicators that traders combine with their own discretion, with five gates and a trial-count haircut applied to every reported Sharpe ratio.

Without that layer, the rest of the stack is just expensive hardware running fancy math.

On top of that sits data we own and control. It’s multi-asset, curated end to end across what we call the Forge, the Pier, and the Vault.

• The Forge is where strategies are built and stress-tested under realistic cost and slippage assumptions.

• The Pier is where data lands, gets cleaned, and is held to institutional quality bars before it ever touches a backtest.

• The Vault is where validated strategies live in a registry that feeds the multiple-testing correction across every trial we’ve ever run, which is what stops a lucky parameter sweep from quietly becoming a marketing chart.

Each one earns its place, and we’ll go deeper on each in coming posts.

Above the data, compute we own and control. A Mac Studio purpose-built for systematic backtesting, sized to handle 150 to 200 hypothesis trials per day. The constraint on quant research has historically been compute. For us, the binding constraint is hypothesis count, not throughput. Patience is a competitive advantage in this kind of work, and ownership is what makes patience affordable.

At the apex, AI used the way it’s actually useful, which is to expand the surface area we can test before we commit to anything. Judgment still does the deciding.

What rigor actually looks like

Most retail products show you the polished output. Our framework is built around showing you the discipline.

Every indicator we ship gets a one-page disclosure pack that publishes the trial count, the regime decomposition, the 30-day forward paper trading result, and a labeled section called “where this fails.”

That last section is mandatory. The point of it is to make sure you know exactly what conditions the tool isn’t designed to handle, before you put real money behind it.

Our published Sharpe numbers will look lower than the competition’s, on purpose, because we apply a haircut that scales with the number of variants we tested. Applying that haircut is the only honest way to report results when you’ve tried twenty versions of an idea before settling on one. If you’ve ever wondered why a backtest looked clean and live trading looked different, this gap is most of the answer.

Every trial that runs through the Forge gets logged. Most of them will fail. Some of those failures will become teardowns we publish openly, because the misses are usually where the actual lessons live. Treating them as part of the deliverable is the kind of work we want our name on.

What’s coming…

BitFinance is already the community. The list you’re on, the conversations in the comments, the people who reply to these emails are the thing. What’s changing is where the community can meet, and what it has access to.

Over the coming months, we’re expanding into Discord, where the community can engage directly with the tools the methodology produces. That’ll start with indicators across digital assets and traditional equities, with more coverage to follow. The Discord is going to work as a live feed of the methodology in operation. You’ll see strategies enter the pipeline and exit it. You’ll see the council reviews where we pre-mortem candidates before they consume serious research time. You’ll see the wins and the failures published with the same care.

We’re also rolling out premium content featured here on Substack, for readers who want a deeper look at the methodology, the tools, and the work behind specific indicators.

Not to worry, the weekly roundup, the educational pieces, and the broader market commentary aren’t going anywhere. They stay free.

Some of you have already expressed interest in working with automated and AI trading bots. You’re on this list too, and the same access applies. Whatever shape your interest takes, we want you positioned to see things first.

That’s the arc. Some of the dates will move, and the standards won’t.

How to reserve your spot

Nothing changes for you today. The Substack continues at the cadence you’re used to, and the work continues.

If you’d like first access when Discord opens and the first indicators ship, this is where to raise your hand.

Interested? Fill out the 30-second interest form here. 👈

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We’re genuinely excited about what’s taking shape, and we’d rather show you than tell you about it. Stay tuned for what’s next.

This Week In 2 Minutes

Saylor’s Bitcoin 2026 Pitch: Bitcoin Is the Collateral. Digital Credit Is the Product. (Apr 29)

Saylor closed Bitcoin 2026 with a pitch that had almost nothing to do with Bitcoin’s price. STRC, Strategy’s perpetual preferred stock, has reached roughly $8.5 billion in notional value in nine months, pays an 11.50% monthly variable dividend, and gets return-of-capital tax treatment.

The structural argument is that if Bitcoin compounds faster than equities or real estate, credit issued against it can sustainably yield more than credit issued against anything else.

The DGCR ETF approval is the next domino worth tracking, since it would hand structured credit allocators a regulated wrapper for the whole architecture overnight.

Read the full article here.

The Quiet Pivot Inside Ripple That Reframes How to Think About XRP (May 1)

The press still writes about Ripple the way they wrote about it in 2022, and that mental model is badly out of date. Three acquisitions (Ripple Prime, GTreasury, and Rail) added up to roughly $4 billion and turned the company into a full-stack institutional finance platform with a token threaded through every layer.

The most consequential moment of 2026 wasn’t a price move but Ripple Prime’s March 2 listing in the DTCC’s NSCC participant directory, which routes XRP-linked infrastructure into the same U.S. clearing rails that handle $2 quadrillion in annual transactions.

Owning Bitcoin doesn’t preclude owning XRP, and the thesis for each one is a genuinely different bet.

Read the full article here.

Weekly Winners 🏆

Records on the equity side, a constructive April close in crypto, and the best earnings beat rate since 2021.

• S&P 500 and Nasdaq. Both indexes printed fresh closing records Friday, with the S&P at 7,230.12 and the Nasdaq at 25,114.44. Q1 earnings are doing the heavy lifting. 84% of S&P 500 companies that have reported are beating EPS estimates, the highest beat rate since Q2 2021, and the index is tracking toward its strongest earnings growth since Q4 2021.

• Apple (AAPL). Up roughly 3% Friday on a fiscal Q2 beat and a better-than-expected revenue outlook. iPhone revenue missed for the second time in three quarters, but China strength and the new iPhone cycle absorbed the slip. The print pulled the rest of mega-cap tech with it.

  

• Bitcoin. April closed positive after a difficult first quarter, with BTC opening May above $78,000 and printing four straight green weeks. The April high near $79,500 is now the line that matters, with the historical pattern showing clearing it early in May tends to extend the rally and failing it tends to invite a pullback.

• Software earnings rebound. Five9 jumped roughly 30% Friday on a clean print that quieted AI-disruption fears in the SaaS complex. Wolfspeed added 26% on new executive appointments and Cboe Global Markets ran 9% to lead financials. After IBM and ServiceNow dragged software two weeks ago, this was a meaningful breadth signal.

Weekly Losers 📉

Trust-and-safety regulation hit one platform hard, an airline ran out of road, and Berkshire’s transition is getting expensive.

• Roblox (RBLX). Down roughly 24% Friday after slashing full-year bookings guidance to $7.33-$7.6 billion from $8.28-$8.55 billion prior. Management cited product changes around age verification and expanded content monitoring tied to multiple regulatory probes on child safety. The bigger signal here is broader than one guidance miss, since trust-and-safety regulation eating into growth is going to come for more than one platform built on permissionless content.

• Spirit Aviation Holdings (SAVEQ). Down 62% Friday to 52 cents on a Wall Street Journal report that the budget carrier is preparing to liquidate its fleet and end operations after bondholders walked from a proposed $500M government rescue package. Penny-stock moves are noisy by definition, and the Spirit story is also a reminder that the post-COVID survivor pool in U.S. consumer airlines is still narrowing.

  

• Berkshire Hathaway (BRK.B). Greg Abel’s first annual meeting as CEO went off Saturday in Omaha, with Buffett seated in the audience and praising his successor on a recorded segment. The capital allocation question is what’s actually under the microscope. BRK.B has trailed the S&P 500 by more than 30 percentage points since Buffett signaled his step-down last May, and Abel is now under real pressure to deploy a record cash pile thoughtfully rather than chase the index.

• Ether (ETH). Opened Thursday at $2,252, the lowest print since April 13, while BTC held near its monthly highs. The relative weakness has been a steady theme through Q1 and into Q2, and the bull case for ETH increasingly leans on regulatory catalysts that haven’t shown up yet.

On Deck

What to watch the week of May 4.

• Consensus Miami (May 5-7). I’ll be at the Miami Beach Convention Center for all three days representing the great team at Crypto Insights Group. The themes worth tracking this year are stablecoin policy, tokenization of public-market assets, and the AI-and-blockchain integration thread that’s moved from theoretical to operational. If you’re going to be on the ground, reply to this email and we’ll find a coffee.

  

• FOMC meeting (May 5-6). The Fed’s May meeting lands the same week as Consensus. Markets are pricing in no change to rates, with most of the focus on the post-meeting press conference and any signal Powell offers on the balance-sheet runoff timeline.

• Q1 earnings continues. Roughly 126 S&P 500 companies (including two Dow 30 components) report this week. With 84% of prior reporters beating, the bar to keep the rally going is higher than it was three weeks ago.

• The early-May $80K test for Bitcoin. April high sits at roughly $79,500. The historical pattern since 2020 says clearing the prior-month high in the first five trading days of May tends to extend, while failing it has averaged a 20% drawdown over the rest of the month. May’s overall track record is mixed (it ranks sixth by average return since 2013), but the early-May pivot is a reasonable line to watch.

  ---

🛑 REMINDER 🛑

If you’d like first access when Discord opens and the first indicators ship, this is where to raise your hand.

Interested? Fill out the 30-second interest form here. 👈

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Matthew Snider is the founder of Block3 Strategy Group, author of “Warren Buffett in a Web3 World,” and publisher of the BitFinance newsletter. He holds a Series 65 and MBA, and has been an active participant in digital asset markets since 2015. This article is for educational purposes only and should not be considered financial advice. Always consult with a qualified professional before making investment decisions.

I walked the floor today. Ripple’s “Raise the Standard” billboard towering over the Strip is the kind of advertising spend that doesn’t happen unless a company has decided it’s done apologizing. They painted the entire strip with their logo and vision of a unique developing ecosystem.

The conference itself read more like a fintech summit than a token meetup. Brad Garlinghouse, David Schwartz, Matt Hougan from Bitwise, John Deaton on the legal panel. The conversation around me was focused on institutional progress around prime brokerage, post-trade settlement, and a stablecoin custodied at BNY Mellon. ($RLUSD)

Most of the financial press still writes about Ripple the way they wrote about it in 2022:

• A token company.

• A lawsuit.

• A CEO doing media tours about regulatory clarity.

That mental model is now badly out of date.

Here’s what’s actually happening, and why it matters for anyone trying to size XRP as part of a real portfolio.

The Thesis in One Sentence

Ripple in 2026 is a full-stack institutional finance company with a token attached, not a token company building infrastructure on the side. The token is one piece of a system that now includes prime brokerage, treasury management, custody, a stablecoin, and direct integration into U.S. clearing rails. That reframe changes the question every allocator should be asking.

Stop asking whether XRP is going to pump. Start asking what a $4 billion bet on owning institutional plumbing is actually building toward.

The Pivot Behind the Pivot

Three deals tell the story.

• Ripple Prime (the rebranded Hidden Road acquisition, $1.25B, closed October 2025) clears roughly $3 trillion annually across foreign exchange, derivatives, fixed income, and digital assets for over 300 institutional customers. Ripple is now the first crypto company to own and operate a global multi-asset prime broker.

• GTreasury ($1B, October 2025) brings 13,000 banks and over $12.5 trillion in annual payment volume. Real corporate clients. American Airlines, Goodyear, Volvo. This is enterprise treasury infrastructure, not a crypto experiment.

• Rail ($200M, August 2025) adds Toronto-based stablecoin payment rails for cross-border transfers.

The three acquisitions stack. Each one extends Ripple deeper into regulated financial infrastructure, with XRP and RLUSD threaded through every layer. RLUSD now sits as collateral inside Ripple Prime’s brokerage products, with derivatives clients increasingly choosing to hold balances in RLUSD rather than other stablecoins.

The Receipts Most Coverage Missed

The single most consequential story for XRP in 2026 wasn’t the ETF launches or any price move. It was a March 2 entry in a clearinghouse directory.

Ripple Prime was added to the DTCC’s National Securities Clearing Corporation participant directory on March 2, 2026, assigned clearing broker code 0443.

The NSCC processes over $2 quadrillion in transactions annually. (yes, quadrillion)

For the first time, XRP-linked infrastructure has direct access to U.S. clearing rails used by traditional prime brokerages. DTCC’s 2025 patent filings had already named Ripple and XRPL alongside Bitcoin and Ethereum as compatible architecture for tokenized post-trade settlement. The March 2 listing made that architecture live.

DTCC is targeting tokenization of Russell 1000 stocks, major ETFs, and U.S. Treasuries within roughly 50 weeks of late March 2026. Ripple Prime is the prime broker that’s already inside the system, ready to clear the flows.

Add the rest of the data points and the story becomes a glaring opportunity.

• Goldman Sachs disclosed a $154 million spot XRP ETF position in its Q4’25 13F.

• Brad Garlinghouse announced a $500 million institutional investment from Fortress, Citadel, Pantera, Galaxy, Brevan Howard, and Marshall Wace.

• Seven U.S. spot XRP ETFs are now trading with $1.29 billion in cumulative inflows since November 2025.

This is not a retail story anymore.

The Disconnect

Here’s the part that should interest anyone who actually does diligence.

XRP ETFs pulled in $82 million in April, the best month of 2026, fully erasing March’s $31 million outflow. Bitwise just overtook Canary as the largest XRP ETF, signaling institutional money replacing the retail flows that drove the November launch. XRP is trading at $1.41, locked inside the same $1.30 to $1.50 range it’s been in since February.

Money in. Price flat.

Two reasons. Roughly 60% of XRP’s circulating supply was bought near $1.44 and sells into every rally, creating a structural sell wall. Bitcoin is winning the macro rotation, with BTC ETFs pulling in $996 million in a single week in mid-April. The institutional buying is real but it’s being absorbed at a high rate.

Worth noting: a divergence between sustained ETF inflows and flat price action usually resolves in one direction. Once supply is absorbed, the next catalyst tends to move price faster than people expect.

Why I Hold Both

I own Bitcoin and I own XRP. There I said it.

They’re not the same bet, and I don’t pretend they are.

Bitcoin is a monetary asset. The thesis is monetary debasement, sovereign reserve adoption, the fixed supply story. Saylor’s keynote in Vegas this week made the case better than I can.

XRP is a bet on a payments and post-trade infrastructure company. The thesis is institutional rails, regulated stablecoin adoption, and the value that accrues to a token threaded through a system that’s actively integrating into U.S. clearing infrastructure.

Owning Coca-Cola doesn’t preclude owning Apple. Buffett didn’t refuse to buy American Express because he already owned Bank of America. Tribal investing is an emotion, not a framework. Each holding has to earn its place in a portfolio on its own merits, and the merits here don’t compete.

The XRP and Bitcoin communities have spent a decade treating each other as substitutes. The data says they aren’t.

What to Watch

Three catalysts worth tracking.

1. The CLARITY Act Senate Banking Committee markup before the May 21 recess. If it lands, XRP gets structured as a digital commodity in settled law and the $4B+ in institutional infrastructure gets a regulated runway. Polymarket has 2026 passage at roughly 47%, down from 82% in February.

2. The DTCC tokenization rollout. Russell 1000 stocks, ETFs, and Treasuries inside a 50-week window starting late March 2026. Ripple Prime is already wired in. This is the integration that turns “XRPL is enterprise-grade” from a marketing line into a settlement reality.

3. Bitwise’s price scenarios. The firm leads issuer rankings in XRP ETF inflows and just published a 32-page investment case with a $4.94 base case for end-2026, $6.53 max case. Standard Chartered models $7 if CLARITY passes plus ETF inflows scale to $4-8B.

The Frame I’d Use

XRP isn’t a payments altcoin anymore. It’s the equity-adjacent exposure to a company that has spent four billion dollars buying its way into U.S. clearing infrastructure, with a token that captures value as the system scales. Whether the thesis vindicates depends on legislation, integration timelines, and supply absorption. Whether the company has built something genuinely new is, at this point, a question with receipts.

I walked out of the conference with the same conclusion I walked in with. The most interesting story in XRP isn’t on the price chart. It’s in the directory entries, the acquisition list, and the institutional cap table.

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Matthew Snider is the founder of Block3 Strategy Group, author of “Warren Buffett in a Web3 World,” and publisher of the BitFinance newsletter. He holds a Series 65 and MBA, and has been an active participant in digital asset markets since 2015. This article is for educational purposes only and should not be considered financial advice. Always consult with a qualified professional before making investment decisions.