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WARNING: A rare market edge is about to disappear

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Recently, legendary trader Tim Sykes bought a small stock.
He closed his laptop and enjoyed the weekend.
Monday morning, he sold for $9,177 more than he paid. A 121% gain in under 65 hours.
The most surprising part?
He didn't check a chart. He didn't set an alert. He made two simple decisions and walked away.
BREAKING NEWS
πΈ Big Tech Just Committed Over $1 Trillion To AI's Future
Here's a number that's hard to believe is being spent on one idea: $1.09 trillion.
That's how much Microsoft, Amazon, Alphabet, Meta, and Oracle have collectively promised to pay for AI data centers under leases that haven't even started yet, according to Reuters.
Here's what makes this story so fascinating. Because many of these leases haven't officially begun, they don't appear as debt on company balance sheets yet. Instead, they're disclosed in the footnotes of financial filings as future lease commitments. Reported lease liabilities for these companies total roughly $285 billion, while their future commitments have ballooned to $1.09 trillion.
That doesn't mean the companies are hiding anything. These obligations are fully disclosed and well known to analysts. It simply means the scale of their future spending is much larger than many investors realize at first glance.
Three points worth noting:
π’ Microsoft has the largest commitment: About $329 billion in future AI data-center leases. But Oracle's $260 billion is considered the boldest relative bet because it's nearly seven times the lease liabilities already on its books.
π The spending is accelerating: Future lease commitments jumped from roughly $662 billion just six months ago to $1.09 trillion, showing just how quickly AI infrastructure investment is expanding.
βοΈ These aren't optional expenses: Once these leases commence, companies are obligated to make those payments whether AI demand exceeds expectations or falls short. That's why this is one of the biggest corporate bets in history.
π§ What This Means For Investors: For investors, that $1.09 trillion isn't just a scary number, it's a roadmap. It shows exactly where the money is flowing and money that size drags a whole supply chain along with it. The obvious winners are Big Tech, but the less obvious ones might be better: the companies making the chips, generating the power, wiring the networks, and building the equipment of these data centers. When five giants commit a trillion dollars to construction, somebody's getting paid to pour the concrete. Why do you think Caterpillar ($CAT) is up over 40% this year?

The Munch Take: Say what you want about the risk, a trillion dollars of commitments leaves zero doubt about one thing: the smartest, richest companies on Earth are convinced the future is AI. Nobody bets this kind of money on a fad. That's the bull case in a single number. But here's the catch, and it's a big one. This is a long-run game that hasn't paid off yet. Companies are pouring in fortunes today on faith that the demand shows up tomorrow, and "tomorrow" keeps getting more expensive. If AI demand keeps booming, these data centers become the foundation of the next decade and this spending looks visionary. If it cools even a little, these giants are stuck paying rent on enormous buildings full of chips that lose value fast.
Watch Before 9:29am Tomorrow Morning (Ad)
Dear Reader,
Already, the worldβs richest investors have committed $725 billion to it β with no signs of shopping.
This situation is moving quickly.
And if Iβm right about this trend, it has potential to make you more money than any investment you have ever made before.
Good investing,
Alexander Green
Chief Investment Strategist, The Oxford Club
THE MARKET WATCH
π’ The AI Wunderkind Who Lost $35 Billion Is Already Back
Buckle up, because this is the wildest Wall Street story of the summer.
First, a quick introduction. Leopold Aschenbrenner is a 24-year-old former OpenAI researcher who wrote a viral 165-page essay about AI in 2024, then launched a hedge fund named after it, Situational Awareness.
Here's where the story gets wild. His fund exploded to $45 billion, posting a jaw-dropping 439% return in the first half of 2026 by betting everything on AI infrastructure. Then last week, it all came apart. The chip selloff (the same one that whipsawed Korea) plus reported leverage as high as 400% triggered a wave of margin calls. He was forced to dump his entire stock portfolio to Ken Griffin's Citadel at a discount, and the fund collapsed from $45 billion toward $10 billion in a matter of days.
The twist? Days later, he's already back, quietly plunking down $400 million on a private company, his first move to rebuild. If nothing else, you've got to admire the "back to work on Monday" mentality.
Hereβs a breakdown:
β‘ Leverage was the killer: Borrowing up to 4x meant that when his AI bets dropped, the losses multiplied violently.
π§ His thesis wasn't wrong, his timing was: He bet AI needs massive infrastructure. That's likely true long-term. He just couldn't survive the short-term dip.
π He's already trying again: Just days after losing roughly $35 billion, Aschenbrenner reportedly committed $400 million to a private company, showing his conviction in AI hasn't changed.
β° Bonus Report: Critical Alert to all traders (via Prosperity Pub)
Aschenbrenner may end up completely right about AI. His whole thesis is basically the same one behind that trillion dollars of data-center spending we just covered. But being right about the destination means nothing if leverage wipes you out on the journey. He used borrowed money to supercharge his bet, and when the market dipped just a little, that same leverage detonated him from $45 billion to a fire sale in days.
The Munch Take: This is the single best investing lesson of the summer. Borrowing money can amplify your gains, but it also gives the market the power to end your story before your thesis has a chance to play out. If your long-term conviction is real, don't compromise it with short-term overleveraging. Think of it this way: you need bullets left to hit the target. You can't win the marathon if you sprint so hard that you collapse halfway through.
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