AI was going to kill all of humanity. The Clarity Act wasn’t going to pass. Crypto was going to zero. The war with Iran was going to last forever. And the Fed was raising interest rates.

Okay. All of that news happened. The Fed hiked. Clarity failed. Iran is digging in its heels. 

So that’s the end of it. Humanity is dying, crypto is going to zero, and AI is killing everyone. 

And yet, the stock market is at all-time highs. Nvidia is near all-time highs. Crypto is substantially up since the Clarity Act failed.

The media hates this.

Every day there’s a new story. 

I saw a headline saying that for AI companies to pay back the infrastructure build, the country will have to spend 9% of GDP on AI. 

I read the article because I wanted to check what they were talking about. All the math was completely wrong. Their assumption, that demand won’t catch up to infrastructure costs, is wrong. The demand for AI is absolutely going to catch up with the infrastructure costs.

And the 10% chance AI destroys humanity? There is a 0% chance. AI on its own is really stupid. It veers off track. It doesn’t stay on target unless a human is constantly monitoring it. It’ll write 100,000 lines of code in the time a human writes 10. Its reasoning is still very poor.

So let’s follow the money.

Between now and 2032, $10 trillion is going to be spent on AI infrastructure. You want to own the companies that $10 trillion is going to rain down on.

Here’s how it works.

Anthropic goes to Amazon. “Our demand is great. We want to host a lot of AI on your cloud. We need data center space.”

Amazon goes to Nvidia. “We’re going to need a lot of data centers. We’re talking to you and Dell and maybe Super Micro.”

Nvidia says, “Well, we’ve got the GPUs. We’ll call our buddies.” So they call Marvell. “We need to connect all these GPUs. Can you do it?”

“No problem, Jensen.”

Then Marvell says, okay, we don’t want the old interconnects. We need the latest, fastest thing. So they go to the small cap and microcap public companies building new technology and ask, “What have you got for us?”

Nvidia won’t talk to those little companies directly. Marvell shepherds them along until they finally get a conversation with Nvidia, who’s talking to Amazon, who’s talking to Anthropic and OpenAI.

That’s the chain. That’s how it works.

Let’s say Nvidia is going to keep going up. Marvell is probably going to keep going up too. But they aren’t where you find the 50x, 100x potential returns.

But most of the big stocks are maxing out. Not all of them. But a lot of them. So people are going to start looking lower and lower down the chain.

The money falls from the top. It lands at the bottom.

And it lands in bursts. A window cracks open, then the window slams shut.

Knowing which stocks sit at the most profitable part of the chain is half the game. Knowing when the window opens is the other half. I spend every waking day on the first part. For the timing, I call one man: JC Parets.

JC called the 2008 crash early. He called the 2022 bottom live on Bartiromo, to the day. He called Nvidia when everyone else flinched. He’s the best market timer I know.

In this new video, he walks me through The 100X AI Window: the exact day he believes the next window opens (today), and his top trades for it. 

You have until midnight. 

Click here to watch. 

Consider: ChatGPT alone has roughly 900 million weekly users. About 5% pay for it. 

Nothing this popular has ever been this free. 

The PC took years to reach the office, and it was insanely expensive. AI got there in a third of the time, and most paid almost nothing. By last May, an astonishing 45% of American workers used it on the job, according to a survey tied to the St. Louis Fed.

So here’s the question that matters for your money and everyone else’s… 

What happens when 900 million freeloaders start paying? And who collects?

The answer has everything to do with one of the LAST great windows of opportunity in the AI trade. 

Watch the Clock 

METR, a research group that stress-tests AI agents, tracks how long a task an AI can finish on its own. Since 2023, that length has doubled roughly every four months. Lately, closer to three.

Here’s what that looks like. 

A programmer leaves a job queued at 6 p.m.—the kind that would eat two full workdays. She goes home. By morning, the AI has finished it. 

Two years ago, it handled tasks measured in minutes. Now it can work around the clock. 

People might pay $20 a month for a chatbot. They’ll pay far more for a worker. Somewhere on this curve, the toy becomes staff.

Of course, there are objections to this. 

Factories. Kitchens. Streets. 

One objection: AI keeps getting cheaper. Epoch AI estimates the cost of a fixed level of AI smarts is falling between 13x and 50x a year. Faster than electricity ever fell. Faster than batteries. Faster than DNA sequencing.

How does anyone get rich selling something that gets 50x cheaper every year?

It’s simple: the same way companies did during the Electric Age. As electricity got cheap, people wired everything. Factories. Kitchens. Streets. 

The price per unit collapsed and the total bill exploded. Cheap AI follows the same law. But 100x faster. Every price cut opens up work that wasn’t worth automating last year.

And the bill’s already exploding.

Enterprise spending on generative AI tripled in 2025, to $37 billion. Menlo Ventures called it the fastest-scaling category in software history.

This year, one product shows how fast it’s still moving. In September 2025, Anthropic’s coding tool, Claude Code, was bringing in revenue at a pace of $500 million a year. By February, that pace hit $2.5 billion. Five months. Five times the money.

That’s the freeloader-to-payer shift. It’s happening at scale. Right now.

Hunting For the Next 100x 

Most AI catalysts are guesses: earnings whispers, product rumors, leaks. This one’s written on a calendar. 

In 1965, Gordon Moore drew a line. Chip power would double on a schedule, roughly every two years. It held for half a century. Whole industries planned around it. The investors who believed it early got rich.

METR’s line is the new Moore’s Law. It doubles every three to four months, about six times faster. Since early 2023, AI went from tasks measured in minutes to two full workdays.

Read it forward. 

One more doubling gets you almost a full work week. Two more get you two weeks. A month of work arrives by mid-2027. 

Each doubling converts another slice of the freeloaders into customers. Each one moves the money a little further toward the companies sitting on the chokepoints.The further downstream it goes, the smaller the companies that catch it. 

THAT is where you find the next 100x. But this window won’t be open for long. The calendar always turns whether you’re watching or not.

David Rubenstein has hired former presidents. He's interviewed thousands of people. And he just told me on my podcast he could never bring himself to fire anybody.

Early on at Carlyle, the private equity giant he cofounded, he would have to fire someone. 

The person would come into his office and explain how great they were at their job. And then somehow they'd walk out with a promotion.

His partners stopped letting him do the firing. 

Then David bought the Baltimore Orioles.

In baseball, when the team loses, somebody has to get fired. Last year it was the manager, Brandon Hyde. Two years earlier, Hyde was Manager of the Year.

David's explanation: it's easier to remove the coach than the players. And owners don't tend to remove themselves.

He wrote a book about all this, Inside the Owner's Box. When he bought the team, he went and interviewed other owners to learn how to be one. Learn and write at the same time. I love that.

My first question: will there even be a baseball season next year? The players' contract runs out in December. The owners want a salary cap. The players hate the idea.

"Nobody knows," he said. 

He said that a lot. Nobody knows who becomes a superstar. Nobody knows if AI creates jobs or kills them.

He's right. Most of the time.

Here's what I learned from David.

Money Doesn't Buy Wins

Since David took over, the Orioles have more than doubled player salaries.

The results haven't followed.

The Mets have one of the richest owners in baseball. No championship. The Dodgers spend big and win. Same strategy. Opposite results.

And the draft? In basketball and football, the top picks almost always make it. In baseball, the number one pick sometimes never reaches the majors. Cal Ripken wasn't a first-round pick. Tom Brady went in the sixth round.

Babe Ruth couldn't get a job managing. Earl Weaver never played a single major league game. He's in the Hall of Fame as a manager.

Credentials predict less than we think.

Shut Up and Walk

During the Orioles deal, a banker on the other side started explaining to David what debt is.

Sitting on David's side was Mike Arougheti, who runs the largest private debt business in the world.

A desperate buyer swallows that. David called it childish and hung up.

He was ready to walk away. He wasn't sure he was the right buyer, and he had plenty of other things to do.

Plus, he didn’t want to seem desperate. He always avoided saying things like "I can't wait to get this deal done. My children want me to get this deal done. This is the highest priority of my life." Say that, and you're probably not an effective negotiator. 

That's his rule. If the other side knows you'll put up with anything, you won't get the best deal.

He went back in eventually. A chance to own your hometown team doesn't come twice.

Just don't tell them your kids are begging you to close.

Why We Care

I asked David the big question. Why does a guy in Baltimore care if the Orioles win? It doesn't put bread on his table.

He said Baltimore has been the stepchild to New York, Boston, Philly and Washington for 200 years. When the Orioles win, Baltimore is as good as anybody.

Then he turned it on me. Why do I care about the Mets?

When I was a kid, it felt like I was winning when they won.

That's it. That's the whole business. Millions showed up for the Knicks parade. None of them own a piece of the team.

"Logic isn't everything in life," David said.

That's why he'll never sell. His parents are buried in Baltimore. He'll be buried there too. The team is his way of paying the city back.

As we wrapped up, he complimented my haircut. Then he asked if I'd ever owned a comb.

I'm 58. He told me that makes me a teenager.

He's sending me a comb. I'll let you know when it arrives.

Click here to listen to the whole podcast. 

Look for the line that says "supply" or "generation." In Ohio, it's called the Price to Compare. 

Part of that number powers Big Tech's data centers. You never signed up for that.

Nobody asked.

Here’s the thing: Every rule that raised your bill can also make you money, if you know where to look. 

Here's how the game works, and how to win it.

The Game

Here's where a big piece of that number comes from: an auction almost nobody watches.

It's run by PJM, which runs the power grid for 65 million people in 13 states and D.C.: Delaware, Illinois, Indiana, Kentucky, Maryland, Michigan, New Jersey, North Carolina, Ohio, Pennsylvania, Tennessee, Virginia and West Virginia. Some of those only in part.

Live somewhere else? Doesn’t matter. 

PJM is America's biggest grid operator, and it's where AI has hit hardest so far. Every grid is facing the same wave of data centers. 

This is the preview.

How the Game Works 

The auction exists to make sure the grid can survive its worst days, the hottest afternoons and the coldest nights, with a cushion to spare.

So PJM pays power plants, years in advance, to stand by for it. Think of it as paying a fire department to sit by the phone.

The auction sets one price, and every plant gets paid it. Think surge pricing. You pay your slice, buried in the line you just found. 

Until recently, nobody minded. Then AI showed up. 

One AI data center can use as much electricity as 100,000 homes. And the ones already under construction or contract in PJM will use five times more power than every data center running there today. FIVE TIMES. 

In a single auction, the price rose nearly tenfold, and the region's yearly bill jumped about $12.5 billion.

So the governors forced a cap, at about 11 times what the price was in 2024. The auction has hit it three times in a row. In July, even at the cap, PJM came up short by about seven nuclear reactors' worth of power.

Where It's Headed

Here’s why this is important now: the next eight weeks could set your bill for years.

Last week, regulators froze PJM's emergency plan to buy new power plants. The fight is over who pays. On November 3, the states elect the people who decide. December brings the last auction scheduled under the price cap. Again, it hit the ceiling three straight times. December could make four.

After that, the cap expires unless someone renews it. Keep it, and the grid runs on a thinner cushion. Lift it, and your bill climbs. Pick your poison. 

Or… make someone else drink it.

That's where this is headed. Politicians will push data centers to bring their own power. PJM's plan already points there: new data centers coming online after mid-2027 would have to supply their own, or get cut off first in an emergency.

So AI companies are becoming power companies.

Meta applied to trade electricity. OpenAI is hiring a power trader. SpaceX, which now owns xAI, is building its own gas pipeline and trading desk, with power plants on the way. Amazon, Google and Microsoft already trade power wholesale.

How to Play the Game 

Nobody elected PJM. Most people couldn't name FERC.

Between them, they help decide a growing piece of your power bill for years to come.

You can't vote them out, but now you know how the game works. Quiet offices write the rules. The headlines arrive late. The people who read the calendar move first.

Big Tech figured that out. It's why they're building trading desks.

And the thing is, you can play the same game. Watch the quiet offices. Move before the headlines. That’s it. 

Right now, James has his eye on another quiet office nobody’s heard of. Like PJM, it's a private nonprofit nobody elected, overseen by a federal commission most people couldn't name. And it has a date circled: Friday, October 9.

James just changed his entire AI thesis because of it. That's how big this is. 

In fact, James just sat down face to face with a trader who's made a career out of tracking that one quiet office.

Click here for the FULL interview… and see what’s circled for Friday. 

He climbed onto the roof of a Washington school and spoke into a mirror.

The mirror shook with his voice. The sunlight bouncing off it flickered in step with his words. Seven hundred feet away, a receiver caught the flicker and turned it back into sound.

Bell called it his greatest invention, greater than the telephone. He wanted to name his second daughter Photophone. His wife talked him out of it.

Then a cloud passed. No sun, no call. Copper worked in any weather.

Inside the machines, copper kept winning for 146 years.

Bell was early. But he was also right.

And something—maybe you’ve heard of it—is changing the entire architecture: artificial intelligence.

For years, using light to carry messages inside a computer was a lab trick. AI changed that. 

This fall, it hit the loading dock. And last Thursday, a rocket fired the starting gun on its next act.

Which means right now is the time to start paying close attention. 

AI's Clogged Artery

Let's start with the basics.

No single chip can train an AI. The job gets split across thousands of them, and they have to swap notes constantly.

Picture 10,000 cooks making one meal, passing ingredients down the line. The cooking is fast. The passing is the problem.

Copper does the passing.

For a century and a half, it was fast enough. 

AI broke that.

Push copper harder and the signal smears, like shouting down a long hallway. Cleaning it up takes power and throws off heat. Datacenters are already fighting over power plants.

So engineers went back to Bell's idea.

Revenge of the Sunbeam

A laser turns the chip's electrical signal into flashes of light, billions per second. A detector at the far end turns the flashes back.

Light travels clean, runs cool and goes the distance. The closer you put that laser to the chip, the less copper you need.

This summer, it left the lab.

In August, Nvidia's light-based network switch went into full mass production.

The first units went to CoreWeave, Lambda and Oracle. Coherent expects revenue from its version to start ramping in Q4.

The idea Bell patented in 1880 now ships with an invoice.

Here's the part nobody's connecting.

Screw the Clouds 

Bell had the light. He had the beam. The weather beat him.

Now the billionaires are going around the weather.

On October 1, a SpaceX rocket carried a small Google satellite into orbit. Inside were four of Google's AI chips. The project is called Suncatcher.

Of course, Google isn't alone. 

Musk's SpaceX has asked regulators for permission to launch up to a million AI satellites. Bezos's Blue Origin wants an oddly-specific 51,600. A startup called Starcloud has already flown an Nvidia chip into orbit.

They're all chasing the same thing: endless sunshine for power, and lasers to pass notes between satellites.

Copper can't cross empty space. Radio can't carry enough. So the plans run on light. 

Is it early? Very. But that's the point.

Nvidia is shipping light. Google has chips in orbit. Musk and Bezos have filed their paperwork. The biggest laser maker says it's sold out through 2027.

The starting gun just went off. The crowd shows up when the satellites start talking.

Bell aimed a mirror at the sun and talked. Now the billionaires are aiming lasers past the clouds.

Same idea. Better altitude.

Put your chair out early.

I said that to Bill O'Reilly on my podcast. He'd just told me he knows everybody. "Even you, James."

That's how you know he means everybody.

This was his third time on my podcast. At the end, he thanked me for reading his book.

"Many interviewers don’t do that," he said.

Bill’s written more bestsellers than I've written grocery lists. He goes on show after show. And the host flips to the back cover five minutes before airtime and asks, "So what's the book about?"

That's how you get the same interview forty times in a row.

Maybe I’m the only podcaster who reads every guest’s book. I’ve done it for over a decade. And I always learn something new and hear stories nobody’s heard before. 

Like this one… 

How Often Does This Happen? 

After the election, before Trump was sworn in for his second term, Biden's national security team needed to reach the president-elect. Hostages were sitting in Gaza. Netanyahu wanted Trump's sign-off on the mechanics of a deal.

They couldn't get through.

So Jake Sullivan called a friend of Bill's. Bill set up the call.

He moderated it. He offered no opinion. Trump was on the line and knew every detail, Bill says. About two weeks later, four hostages walked free.

I sat there thinking: how many phone calls like that happen every day that we never hear about?

Most of them. That's how the world works. The real story is almost always the one nobody reports.

Which brought us to talking about the media. 

Why The Media Hates Good News 

Bill knows how the media works better than anyone. He said they hate good news. 

He pointed to a recent report—American households have more assets than ever, and the poverty rate is at a record low. He says CNN never mentioned it.

I pushed back. Americans have had record assets almost every year since 2010. Is that even news?

Bill's answer: the numbers are new, and they keep going up. Meanwhile all you hear about is gas and groceries.

He has a point. Fear sells. Fear always sells. I've been reading headlines for 40 years. If I'd traded on every scary one, I'd be broke. Actually, I have been broke. More than once. Usually because I listened to the scary headlines.

Then I asked him an uncomfortable question.

What About Bill? 

Didn't shows like his start this? The O'Reilly Factor launched in 1996. Opinion all day. Didn't that open the door? 

He said the Factor told you it was opinion. Every newspaper has an op-ed page. TV didn't. So he built one. Back then his audience was roughly 60% conservative and 40% liberal. He wanted it that way. He brought on people who disagreed with him and got into shootouts.

Now? Every channel brings in people who agree with the channel. Easy money. Preach to the choir and the choir pays.

Trump just kicked CNN, MS NOW, and Politico out of the White House. Bill has no love for any of them. Bill said it was a bad move. 

"I would have shunned them," he said. Seats in the back. Never call on them. But never kick them out. 

That's a business lesson, too. Don't fight the people who want a fight. Ignore them. Attention is oxygen.

A Life Fully Lived

I'll admit it. 

I was more opinionated in this interview than I usually am. We talked about New York City, where I lived my whole adult life. We talked about Mayor Mamdani's plan for city-run grocery stores that charge 20% less.

Grocery margins are about 1%. Do the math. Every bodega near one of those stores goes out of business. The bodega owner opens at 6 a.m. and closes at midnight. He's the one who pays.

Bill agreed. You don't have to. Listen and decide.

But the part I keep thinking about came at the end.

In the book, Bill writes that his father's final words were about never reaching his potential. That's a heavy thing to hear from your dad. Some people spend their whole lives running from a sentence like that.

So I asked Bill: Have you reached yours?

I expected him to say no. Everyone ambitious says no. There's always one more mountain.

He said he's pretty much done everything. No more quests. He still wants to do a good show every day. But if someone walked in tomorrow and said, "O'Reilly, you're out," he'd say thank you.

I don't know if I'll ever feel that way.

But I'd like to.

Maybe that's the real potential. Being able to say "enough" and mean it.

The book is Confronting America: What Has to Change. The episode is live now.

Even if you disagree with Bill, the podcast is worth a listen. 

And it’s for all the wrong reasons.

I was one of those kids. In 1999, I’d spend weeks scraping together $5 to buy another shiny new pack. I did chores. I sold my old toys. I’d come up with clever side hustles. 

Once I stuffed paper towels into the local soda machine's coin return. Then I’d come back about six hours later with pliers. It was a steady income. Low overhead. (Until everyone caught on.) 

All of that money went into Pokemon. 

I had the good ones too. Charizard. Venusaur. Mewtwo. Blastoise. 

I loved those cards. I sleeved them. I guarded them like nuclear codes. I knew the market better than anyone. I’m not proud of it, but I made a kid cry over a Squirtle trade. 

Where are they now? No clue. 

One day they were in a binder. The next, I was in my thirties, staring at a news headline about Charizard.

Even beat up, in a shoebox, my cards would probably be worth about $50,000 today. Perfect, at this year's record prices? Probably over $1.2 million. Maybe more. 

Twenty bucks of cardboard. $1.2 million.

Seems crazy? It is. 

And it all raises the question: how did a playground toy beat the stock market, and what does that tell the rest of us about how to invest? 

The Numbers Are Real

Card Ladder runs a Pokémon index. Since 2004, it's up roughly 3,821%, according to the Wall Street Journal.

The S&P 500 over the same stretch? About 483%.

In 2021, Logan Paul—a YouTuber—paid $5.3 million for a single Pikachu card. In February, he sold it for $16.5 million. The most expensive trading card ever sold at auction.

This year, while Bitcoin fell, Pokémon cards rose about 30%.

So what's going on?

Three Things

Scarcity. Only so many 1999 cards survived. Kids bent them. Traded them. Lost them. Moms threw them out. 

A generation made money. The kid who ripped open packs in 1999 is 35 now. Peak earning years. And what does a 35-year-old with money buy? His childhood. Boomers did the same with baseball cards and Mustangs.

The money got weird. Governments print money. People want things that can't be printed. Gold. Bitcoin. And, apparently, a Charizard.

The Only Part That Matters

Right now, there are 30-somethings retiring their parents from their childhood Pokemon cards. 

It’s a thing. 

And the collectors who made fortunes never planned any of this.

They bought it because it was fun. They kept it because they loved it. And because they loved it, they never sold.

In 2022, the market crashed. Some cards fell 50%. The flippers panicked and dumped. The people who loved their cards put the binder back on the shelf.

That's the edge. Discipline cracks when you're down 50%. Love doesn't even notice.

Most investors fail for one simple reason. They buy things they don't care about. Then they sell the moment it hurts.

3 Speeds of Wealth

Does that mean you should run out and buy Pokémon cards? Obviously not. 

The only people getting rich are the ones who still have that old binder from middle school. 

But the Pokémon Portfolio can teach you something. 

Wealth runs at three speeds.

Speed One: Love. One to three percent of your money. Something you'd own even if the price went to zero. A vintage Rolex. A '59 Les Paul. A first-edition Gatsby. Buy the rarest thing you can afford to lose. Hold it forever.

Speed Two: Medium. The core. Great companies. Rental property. Dividend payers. Things you buy, hold for years, and let time do the heavy lifting.

Speed Three: Fast. The one most people never have. A small slice of money. A clear catalyst. A short clock. Get in before the news. Get out after.

Most investors only run at one speed. 

The Love-only investor has a garage full of Beanie Babies and is still waiting for them to come back. The Medium-only investor checks his 401(k) once a year, sighs and waits for his 70s. The Fast-only investor has six screens, three energy drinks a day, and an account that peaked in 2021.

The best method? Running all three wisely. Love is up to you. Medium is what everyone talks about. Which brings me to the fastest “speed three” pattern Paradigm has ever published.

The Weekend Trade 

Every Friday afternoon, Wall Street goes home. 

Then Monday morning, news drops. Deals. Approvals. Announcements. Certain stocks explode.

It’s a pattern a lot of people notice but have no idea how to leverage. 

With the help of AI, James recently found a way to play it. One trade Friday. Cash out Monday. Peak gains so far: 280%, 419% and 927%.

He calls it The Weekend Trade.

I missed Charizard. I don't plan on missing Mondays anymore.

James just recorded a quick video to show you how it works. Click here for the full explainer video. 

1. Frontier AI labs have a big problem. It’s only going to get worse. And…
   
   
2. Investors should pay close attention. Most won’t. And they’ll learn too late. 

The problem? All AI models train on the same internet. Same threads. Same answers. Same slop. And then they regurgitate it back onto the internet. 

Now the internet is filling up with machine output, and the machines are training on that. 

Here's the dirty little secret… 

Models learn by counting what shows up most often. Common things get reinforced. Rare things show up only a handful of times, so the model eventually forgets them.

Researchers at Oxford and Cambridge proved it in Nature in 2024. They trained each generation of a model on text written by the one before it. 

Nine generations in, the models collapsed. A prompt about medieval church towers produced gibberish—a looping list of jackrabbits with different colored tails.

Here’s how it’s already hurting investors using AI to hunt for the next edge… 

The Tails Vanish First 

You ask a chatbot about a stock. It gives you the consensus, scraped from what everyone's already written. Then you read the forums, which quote the chatbots. Then the news, which now runs AI summaries of the forums. 

Every source is a copy of the last. You think you're gathering information. You're circling one answer, drifting further from the company with every click.

The tails vanish first. 

The odd fact, the minority view, the one angle that says a stock is mispriced—averaged out of existence. Soon enough, you’re talking about Nvidia and the AI starts talking about jackrabbits. 

The obvious response is to out-think the machines. Good luck. The better response? Feed on what they can't. 

This problem will inevitably change how everyone invests. Those who look for edges now will win the biggest.

Three ways to do it.

One: Look Where the Machine Can't

The machine only knows what's been written down. This makes observing the real world 100x more important. 

Philip Fisher called it scuttlebutt, based on the barrel of drinking water on old ships where sailors gathered to trade rumors—the talk you pick up by asking around.

Peter Lynch found one of his best winners because his wife liked a product she bought at the grocery checkout. The tried-and-true is even more valuable now. 

The method: Leverage the problem itself. Ask AI what everyone believes. It hands you the consensus in seconds. That used to be the hard part. Now it’s free. 

Then go check that one assumption in the physical world. You're not gathering blind anymore. You're aiming a single real-world look at the exact crack in the consensus.

Two: Buy What AI Makes Worse 

What is AI making worse as it grows bigger? There are a lot of them. Here are three. 

Cybersecurity. AI makes attacks cheaper and faster, so defense becomes non-optional spend. This is a direct, growing bill. We’re still early. 

Specialist data. The next frontier is specialist data because that’s what’s getting cancelled out. Labs are paying doctors, lawyers, physicists, and coders to produce fresh reasoning—not answers, but the messy work of getting to an answer. Businesses are springing up to broker that: connect a lab that needs 10,000 hours of radiologist reasoning to the radiologists. The bleeding-edge players here are private, but it’s a real market, moving fast. 

Deepfake financial fraud defense. Fake-CEO voice calls authorizing wire transfers are happening now, today, with real losses. Every company that moves money will need verification. This is early, real, and underappreciated. 

Three: Buy What the Giants Can't

A $100 billion fund can't touch a $300 million company. Its own buying would spike the price, so it skips the company no matter how good it is. Index funds must sell whatever drops out of the index. 

For decades this didn't help you—researching a tiny company took more time than it was worth. 

This is where research is actually most valuable. Because although the research cost collapsed for everyone, the size wall didn't move.

So the newest tool on Wall Street hands its biggest gift to the smallest investor. That almost never happens.

All three are the same bet—find the ground the giants and the algorithms have abandoned. The real world they can't observe, the messes they create, and the small stocks they're too big to own.

Again.

Remember that world? It's worth a look. Because while nobody was looking, that world vanished. 

In September 2021, the SEC had rejected every spot bitcoin ETF that crossed its desk. The SEC chairman was calling the industry the Wild West. Banks kept crypto at arm's length. And a major blockchain had just gone dark for 17 hours, like a bodega with a broken register.

Look at the scoreboard now.

Then: zero spot bitcoin ETFs. Now: U.S. spot bitcoin ETFs hold $108.4 billion in net assets.

Then: about $125 billion in stablecoins. Now: roughly $310 billion. And they're federal law.

Then: settlement in seconds. Now: finality in 150 milliseconds with five-nines uptime. 

Then: tokenized real-world assets were a science project. Now: nearly $400 billion on-chain, spread across 173 platforms and roughly 750,000 holders. And mainstream analysts expect $16 trillion by 2030. 

Then: banks wanted nothing to do with it. Now: BNY Mellon and State Street run digital-asset custody platforms.

Then: the 2021 peak ended in a roughly 80% crash. Now: bitcoin’s drawdown stopped around 50%. At half off, the suits saw a bargain and stepped in. They skipped the full capitulation retail used to provide free of charge.

Then: Washington wanted crypto dead. Now: Washington wants a piece.

Five years. Same asset. Completely different room.

The New Rules of Crypto

At a policy summit in Washington, Michael Saylor said the next 24 months of the American crypto industry now comes down to four people: the head of the SEC, the head of the CFTC, the Treasury Secretary and the President. 

And they are more pro-crypto than the CLARITY bill ever could be. 

The SEC is floating an "innovation exemption." The CFTC wants more room to build. Treasury sees stablecoins as a gift to the dollar. And the President wants America to be the crypto capital of the world.

Four chairs. Four bulls. That’s where to watch. 

Now, the irony…

The Rebel Gets a Corner Office 

I've been tracking this market since 2013. I've watched bitcoin get banned, unbanned, declared dead roughly 400 times and resurrected on schedule. 

Bitcoin was invented so nobody would need permission from a government. Eighteen years later, it rallies when four people in Washington say nice things about it.

That's how it goes with every technology that matters. 

In the 1990s, the government classified strong encryption as a weapon. A programmer who gave it away for free spent three years under federal investigation. Today, that same math guards every bank login in America. 

We always hear about the pioneers who take arrows. But the other part of the story is often forgotten: the ones who survive the onslaught take the corner office.

In crypto’s case, it’s because every empire eventually makes peace with whoever helps finance it. The Medicis figured that out 500 years ago. Tether figured it out last year.

Which brings me to the trade.

How to Play it. 

The consensus call from the crypto commentariat: bitcoin chops through year-end, somewhere between the $80,000s and just under $100,000. 

Plenty of folks bought near the 200-week moving average, at $64,000. Many will happily sell half as the price climbs back toward $90,000. That churn has to clear.

But the bigger story is happening below bitcoin. For a decade, crypto moved as one herd. Bitcoin rallied, and everything with a ticker rallied behind it. Buy the basket, go to the beach.

That era is thinning. The herd is splitting. Assets plugged into real money—dollars, Treasuries, payments, settlement—are moving on their own schedule.

Use the chop to accumulate the assets that win under any chairman: bitcoin itself, ethereum, and the infrastructure institutions are already plugged into. Faster rails. Tokenized stocks. Dollar stablecoins.

The old playbook was simple: buy everything and wait. The new one? Find the assets the real economy can't live without. Then hold on tight.

It was 1990. I was at Cornell, and Steve came to the Computer Science Department to convince the school to buy his NeXT computers. 

They were these perfect black cubes, the most beautiful machines I'd ever seen. I would later write a chess program on one of them.

But nobody was looking at the computers that day. Everyone was looking at Steve. We all crowded around him just to study him up close, like he was a rock star who had wandered into the wrong building.

He was young. He was rich. He had charisma. I was a kid who didn't know what he was going to do with his life, and here was a guy who had already changed the world once and was trying to do it again.

I wanted to be him. I didn't know how. I still don't.

What I did instead, over the next thirty-something years, was buy almost everything he ever helped make.

The laptop. The phone. The watch. The headphones I lose every three weeks. If the Apple Store sold beds, I'd be sleeping on one right now.

So when Ron Johnson came on my podcast this week, I was a little starstruck.

Ron built the Apple Store. The Genius Bar. The whole thing. 

Before that he ran merchandising at Target, where he hired Michael Graves to design teakettles and toasters, and suddenly a discount store had taste. Steve Jobs noticed. He asked to meet "the guy doing all the design work at Target."

Ron's new book is Shop Different: How Retail Revealed Apple's Genius. In it, he writes that one reason Steve hired him was that he was kind.

Kind. Steve Jobs. Same sentence.

I asked him about it. 

What Ron Taught Me 

Ron grew up outside Minneapolis. One winter a neighbor's husband died, and the kids shoveled her driveway before they shoveled their own. That's just what you did.

Steve spent his days with people who lived in their heads. Chips. Code. Specs. Ron lived in his heart. A retailer has to. The whole job is how a thing makes a person feel.

Here's what I learned.

1. Where you stand is your first sentence.

Steve told Ron the first thing Apple says to a customer is where it puts the store. Pick the wrong spot and every local knows instantly. They know where people park. Where they eat lunch. Where the tourists wander. You have to know the town better than the town does.

I think about this with everything now. Where you show up speaks before you do.

2. Hire from bookstores.

Old tech stores were full of guys tinkering with gadgets, avoiding eye contact. Terrifying if you were new to computers. So Apple recruited from bookstores. A good bookstore clerk asks what you've been reading and walks you to the right shelf.

That's the Genius Bar in one sentence.

3. Never hurry the customer.

Ron figured it took four or five visits before someone bought their first Mac. So he told his people: spend all the time they want. Thank them. Invite them back.

I did go back. For years. I'd walk into the Fifth Avenue store with nothing to buy and walk out smiling with an iPod, listening to music from my childhood I hadn't heard in decades.

4. Protect the sacred stuff.

Ron recently walked every home aisle at Target and compared it to what was there thirty years ago. Old Target won. Easily.

The culprit? The floors.

Target used to have white floors, polished every night. The colors bounced off them. It felt happy. About a decade ago somebody swapped them for dark gray concrete because it looked hip. Ron says that one choice drained the life out of the whole store.

Every business has a few sacred things. Institutional memory fades fast. If nobody writes down the Bible, someone paints over it.

5. Take the hit and fix it.

Apple opened its third store on a Saturday. Monday morning, Ron walked into the exec meeting. Steve looked up: "You haven't sold a computer in the state of Texas. What are you doing here?"

Ron sat down and said he'd fix it. Steve went after the work, every time, and Ron knew it. High performers love that. It makes you better.

6. Don't be in a hurry.

I asked for the best business advice he ever got. 

Five words: “Don’t be in a hurry.” 

Under Steve, Pixar made one movie a year. Two would have doubled revenue. Steve refused. Apple waited six years after the iPod to make a phone. Three more for the iPad. You earn the right to do the next thing.

Right now everyone is throwing hundreds of billions at AI, terrified of missing it. Apple sits back and watches.

Maybe that's Ron's lesson scaled up to a trillion-dollar company.

Customers don't move at the speed of business. Neither does anything worth building.

This is one of my favorite podcasts of the year. Click here to listen and see why.