Today's Market = 1999 Capex + 2008 Credit - The Intellectual Investor - Value Investing by Vitaliy Katsenelson

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Today’s Market = 1999 Capex + 2008 Credit

July 30, 2026

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Vitaliy Katsenelson

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I wrote in the past that the AI rollout feels a lot like déjà vu of the 1999 telecom bubble. Today's AI bubble has elements of both the 1999 overinvestment in internet infrastructure and the 2008 collapse of financial instruments that infected the banking and financial system.

Trillions in data centers, funded through the same opaque vehicles that broke the last cycle.

I wrote in the past that the AI rollout feels a lot like déjà vu of the 1999 telecom bubble. Today it is also starting to feel like the 1999 bubble is being supersized into something closer to what led to the 2008 financial crisis.

What is the difference between the two?

The 1999 bubble had two parallel and interrelated dynamics: overvaluation of certain segments of the market (dotcoms, beneficiaries of the new economy, and a slew of other stocks), and overinvestment by telecom companies in internet infrastructure. When the bubble burst, it deflated overvalued stocks and brought value stocks back from the dead. It also revealed overcapacity in telecom infrastructure while sending many of those companies to meet their maker. And it brought a mild recession.

The 2008 crisis started with a housing bubble, but housing is not what nearly took down the economy. It was the collapse of housing-linked financial instruments that infected the banking and financial system. That is what went into the history books as the Great Recession.

Today’s AI bubble has elements of both. Let me take them one at a time.

AI brings a transformational promise and, with it, incredible optimism, which has led to a data center buildout marching toward a trillion dollars a year. At the tip of the spear are OpenAI (creator of ChatGPT) and Anthropic (creator of Claude). The growth and sheer size we see here are unlike anything we have seen before: Anthropic’s revenue has grown nearly 10x in a year, three years running. But its losses accelerate along with its revenues.

Behind them stand the major tech companies: Google, Microsoft, Meta, Amazon, xAI (creator of Grok), and Oracle, a more recent player in AI infrastructure, with multi-hundred-billion-dollar commitments to OpenAI. The relationships among these companies are complex. They are often partners, competitors, and vendors: at times all three at once.

If AI were only a capital-light business, then whatever happens in AI land would stay in AI land. Instead, these businesses make airlines look capital light. Growth requires data centers to support it, and that is where things get dangerous very fast.

Here is Dario Amodei (Anthropic’s CEO) in February: “If my revenue is not 1 trillion dollars, if it’s even $800 billion, there’s no force on earth, there’s no hedge on earth that could stop me from going bankrupt if I buy that much compute… If I’m just off by a year in that rate of growth, or if the growth rate is 5x a year instead of 10x a year, then you go bankrupt.”

What Dario is telling us is that he has to commit hundreds of billions of dollars without knowing what demand will be. If his revenue forecast is off by 20% or a single year, he is done.

And Dario is on the conservative end of this race. He is the one saying the number out loud and planning against being wrong. His competitors see AI as an existential threat and have put the pedal to the metal building data centers.

This creates incredible inflation in everything the buildout touches, starting with GPUs and memory chips. Nvidia and Micron, responding to insatiable demand, have raised prices and now earn margins as if they were software companies.

Their customers, many of whom had the capital-light profile of software companies, have gone from generating enormous free cash flow to being cash flow negative, issuing debt and even equity for the first time in decades. And since they are all competing for the same chips, the same generators, and the same construction labor, they are paying multiples of what these goods and services would cost in a more rational environment.

This is the 1999 element of the story. These data centers cost a lot of money and incur significant fixed costs. But the profitability of AI is elusive. Companies that went all in on AI are struggling with the bill, and many are starting to ration their usage. Open-source and Chinese models are delivering results comparable to frontier models (developed by OpenAI, Anthropic, Google, and xAI) at a fraction of the cost. Good enough is a powerful argument when it costs a tiny fraction of the alternative.

All of this means that what Dario was worried about may come true. It starts to look like a race to the bottom, as trillions of dollars worth of...