recipes for healthy food: I'm Betting My Retirement on This

October 22, 2026

Teeka Tiwari

If I could make only one investment…

This would be it.

In fact, I’m so confident that I’ve put over $5 million of my own money into this strategy.

I already shared this with some of my readers…

And they’ve reported some incredible success.

One guy made $67,000 in a year.

Another made $200,000 in a year…

And another one said he made “about half a million this year.”

What exactly are these people doing?

Let me show you…

Big T

In case you missed it, here’s Big T’s Digital Asset Daily

The Number That Actually Moved The Stock

Alphabet recently reported one of the best quarters in its history.

Revenue jumped 24% to $119.8 billion. Cloud revenue soared 82%. The company beat almost every number Wall Street was watching.

And the stock still fell 8%, wiping out $330 billion in valuation in a single day.

That disconnect – great earnings yet falling share price – tells you everything about where we are in this AI cycle.

So let’s walk through exactly what happened, because the answer changes how you should think about every hyperscaler stock you own.

Buried inside that great quarter was the number that explains why the stock fell anyway.

Free cash flow (FCF) is the money a company has left over after it pays its bills and funds whatever it needs to keep growing. For 22 years, Alphabet threw off mountains of it. Every single quarter since its 2004 IPO, free cash flow stayed positive.

Last quarter, that streak ended.

Alphabet spent $44.9 billion on capital expenditures, mostly data centers and AI infrastructure. Operating cash flow came in at $39.1 billion. Subtract one from the other and you get negative $5.8 billion in FCF.

That means Alphabet spent more building AI infrastructure than its entire operating business brought in. For the first time – ever.

Magnificent Seven counterpart Tesla posted its own negative FCF that same week, and its stock dropped even harder, by about 14.5%.

Here’s what’s really going on underneath those numbers.

For two decades, companies like Alphabet, Microsoft, and Meta were what I’d call asset light. They sold code, ads, and cloud subscriptions out of an office building.

They kept almost all of their revenue as profit because there wasn’t much physical stuff weighing them down. No factories to run or power plants to maintain. Just software margins, the kind of profit you get when a product costs you almost nothing to reproduce once you’ve already built it.

That’s exactly why Wall Street paid growth-stock prices for them. But AI changes the setup.

Think of the AI market in three layers.

At the top, you have the labs — the OpenAIs and Anthropics of the world — selling access to the models.

In the middle, you have hyperscalers like Alphabet, Microsoft, and Meta. They provide the cloud platforms and data centers those models run on.

And underneath both of them, you have the chipmakers, power producers, cooling companies, and equipment suppliers.

The problem for the hyperscalers is they’re the ones spending hundreds of billions of dollars to build the physical infrastructure this whole stack depends on.

And that’s changing the economics of their respective businesses.

To compete in the AI race, they now have to build and own massive physical infrastructure. I’m talking about data centers, power plants, and cooling systems. Even the chips they use wear out and need replacing every few years.

That’s not a pure software business anymore. That’s an infrastructure business. In other words, they’re creeping ever closer to a utility than to the cash machines investors bid up for 20 years.

Look at the balance sheets. Alphabet spent nearly $45 billion on capex against $119.8 billion in revenue. That means capital spending swallowed about 37.5 cents of every revenue dollar last quarter.

This is what I mean when I talk about multiple compression. It’s not some abstract Wall Street term. It’s what happens when a company’s cash flow profile changes and the market stops paying growth-stock prices for it.

And this matters to your money whether you own Alphabet directly or not.

The Magnificent Seven – which includes Alphabet, Meta, Microsoft, and Tesla – together make up more than 30% of the entire S&P 500’s value.

Most Americans have retirement money sitting in an S&P 500 index fund without ever picking a single stock. And that fund carries this exact same exposure, whether you’ve heard of the Magnificent Seven or not.

If the market decides these companies deserve infrastructure multiples instead of software multiples, that’s a haircut sitting inside a large chunk of everyone’s 401(k).

What I Told You vs. What Wall Street Told You

If the hyperscalers are the ones writing the checks, I want to own the companies cashing them.

That’s been our approach for months, and it’s exactly why I’m so bullish on the power producer my team recommended in this month’s issue of my flagship newsletter, Asymmetric Edge.

This company controls tens of gigawatts of generation capacity in two of the fastest-growing power markets in America. It’s already locked in long term contracts tied directly to hyperscaler demand, the same hyperscalers now scrambling to justify their AI spending to Wall Street.

And it trades at a fraction of the valuation the market is paying for the popular AI names, with as much as 261% upside as the market awakens to the story.

If you’re already an Asymmetric Edge subscriber, you can access it right here – including the name, the ticker, the contracts, and exactly why we think it’s one of the best-positioned ways to own this trend.

If you’re not an Asymmetric Edge member yet, I encourage you to watch this briefing I recently recorded about the top players in the third layer of the AI stack.

Friends, the AI buildout is real. I’ve never doubted that for a second. But being right about the trend and picking the right stock inside that trend are two very different things.

Alphabet just showed you what happens when a great business takes on a completely different cost structure almost overnight. The companies getting paid by everyone spending on AI don’t have that problem.

Let the Game Come to You!

Big T