A practical framework for making better decisions, managing risk, and finding opportunity in unpredictable environments. We contrast these principles with the massive $2.9 trillion AI data center build-out by Big Tech, which is betting big on a single superintelligence future.
Show Notes
Inside the relentless race for AI capacity—The Financial Times
Inside the AI race: can data centres ever truly be green?—The Financial Times
The Kanye/Data Center Crossover by Paul Kedrosky—Paul Kedrosky
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Transcript
Welcome to Money for the Rest of Us. This is a personal finance show on money, how it works, how to invest it, and how to live without worrying about it. I’m your host, David Stein. Today is episode 535. It’s titled “Six Principles for Thriving Under Uncertainty, and How Big Tech is Doing the Exact Opposite.”
I recently took over 16,000 words of transcripts from this podcast—these were episodes released over the past two and a half years, select episodes—and I asked ChatGPT 5 to distill them into core principles. They should be familiar to you if you’re a long-time listener of the podcast, because these are the principles I use to navigate my life and manage risk.
In the context of that, when I think about how big tech is building out AI, in some ways these firms are violating all of these core principles. And so it makes for a pretty fascinating contrast to compare “Well, here’s a principle, but here’s what big tech is doing, and this is why they’re doing it.”
Protect the Foundation
So let’s get started with principle number one, protect the foundation. I have couched this in the past as avoid ruin, avoid catastrophic loss, so we can continue, we can stay in the game. We do that by building buffers of savings, building inventories of skills, developing multiple streams of income using a variety of return drivers in our investment portfolio.
An important aspect of protecting the foundation is to recognize what matters is exposure, what’s our capacity to absorb losses, which is different from loss aversion, wanting to avoid all loss because it feels bad. What matters is what are the consequences of losses? Will it ruin us?
Now, some examples recently in my life where I’ve applied this principle is in our business. As we build out Asset Camp, we have taken measures to reduce our use of cash so that we can continue longer as we build out this investment tool for advisors. I have a variety of diversified skills that I’ve built over the past decade, that I didn’t have before.
Prior to launching Money for the Rest of Us, I was an investment advisor. Now we run a podcast, write a newsletter, we build out software as a service. So we’re not dependent on one income stream, and having that multiple income stream has allowed us to avoid taking outside funding and avoid the investment pressure that comes from taking outside funding. It gives us more time to experiment, to iterate. But we’re trying to protect the foundation, avoid ruin.
We can compare that to big tech. I recently finished up our monthly investment strategy report on Asset Camp and Money for the Rest of Us Plus, and I pointed out, according to Morgan Stanley, technology companies are investing $2.9 trillion over the next three years to build out AI infrastructure. One and a half trillion to be financed.
The scale of investment is absolutely astounding, and it’s contributing to GDP growth. One and a half percentage points of GDP growth in Q1 in the U.S. was due to processing equipment and software, much of it AI, a half percentage point in Q2.
Jensen Huang, who is the chief executive of Nvidia, says, “I don’t know any company, industry, or country who thinks that intelligence is optional”, intelligence being AI. “It’s essential infrastructure”, he said. “We’re clearly in the beginning of the build out of this infrastructure”, Huang continued.
Now, when we look at the type of build out that is occurring in the data center space, these are not traditional data centers that Amazon and Microsoft have built in the past.
Andy Lawrence, who’s executive director of research at Uptime Institute—they provide analytics and inspections in the data center space. The traditional data centers, he points out, are a proven model, with proven returns and proven demand. But the new data centers he says, are so much denser in terms of power use. The chips cost 10 times as much. The demand is unproven, and it’s eating up essentially all available power on the grid, and real estate. He concluded, “All of that is an extraordinary challenge and a gamble.”
Some data I got from Paul Kedrosky is he looked at the percent of GDP that was invested in railroads in the U.S. in the mid 1800s. About 2.6% of GDP went into railroads. In the early 2000s, late ’90s, 1.1% of GDP was invested in telecom and fiber; overinvested, both in railroads and telecom. But so far in 2025, there’s been around 1.2% of GDP invested in AI.
Kedrosky points out that the infrastructure investments in railroads and telecom—they’re very long-lived assets. And there is a network effect as the internet was built out, railroad networks were built out. That’s different from data centers.
There’s not really a network effect there, because every company that’s involved in this space they want to build their own. And the GPUs that are used to run the data centers have a relatively short life before they become obsolete, about three to four years. Upwards of 60% of data center costs are the chips. These are not long-lived assets, but trillions of dollars going into it. And if it doesn’t work out, there’s consequences.
So it’s not a strategy of protecting the foundation, it’s a strategy of going all-in. And the reason they’re doing it is because they believe they have to be the first to scale up. So if they become the biggest, then they’ll be able to maintain that lead. That has worked in the past when it comes to search or building out cloud infrastructure. That’s the first principle, protect the foundation.
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