dot-com bubble vs. a possible AI bubble.
From the famous "Dean of Valuation", Professor Aswath Damodaran, of NYU Stern School of Business,
“And that’s the real big difference between the dot-com boom and bust and the AI boom. We don’t know whether there’ll be a bust. History suggests there will be a bust.
The dot-com boom and bust had no huge capital expenditure in that cycle. In fact, there was very little traditional CapEx, or even R&D, driving it. People started apps. They basically started going on it.
This has been the biggest infrastructure run-up I think I’ve ever seen in business. You can go back and compare it to the automobile business 100 years ago. The amount of money that’s being put into AI CapEx is immense, which means that when the correction comes, the pain will be more intense.
And herein lies the second problem. The dot-com boom and bust was almost entirely equity-funded. You think, so what? Well, when the bust came, those shareholders lost 60%, 70%, 80%, or 90% of their money. You felt sorry for them, but the loss was restricted to the shareholders.
The problem with the AI CapEx boom is that not only is it immense, but a big chunk of it is funded with debt, and the debt is coming from private capital rather than banks. There’s a very real chance that if there’s a correction and companies start having problems, that problem is going to show up as distress and default, and that really doesn’t stay restricted. It spills over into the rest of society.
I’m not saying it’s going to be 2008, but 2008 is an example of what happens when lenders overreach, when they lend money at too low a rate, and the correction comes. The pain spills over.
So that is my concern with this big market illusion: the potential societal cost of having to deal with debt coming due that you’re unable to pay. It’s much more painful than your share price dropping 90% and you feeling the pain."
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From "Excess Returns" YouTube channel, (link in comment)
Here I explained the unfolding oil shock in the most simplified way that should be understandable even by a 5 years old - hope is helpful to all those who still don’t see big troubles at the horizon
OTTAWA RENTS ARE HITTING A WALL.
Downtown landlords are now offering 2-3 MONTHS FREE RENT just to fill units.
The problem? They don't want to lower advertised rents because it hurts building valuations.
Renters don't want to sign because many of these newer buildings aren't rent controlled.
So landlords are offering freebies. Renters are waiting for price cuts.
Something eventually has to give.
Thomas Massie says he’s gonna publicly read off the names of Epstein’s clients before his time in Congress is up.
No name would surprise me.
The real surprise would be if any of this actually led to real prosecutions of the powerful people involved.
HIGHER 🇨🇦EDUCATION GOING TO ZERO...
A professor teaching third-year health-care law students admits AI cheating is “widely” happening across universities…
Then gives an unproctored online exam in 2026 and acts shocked when it happens.
At some point, universities need to stop pretending this is just a “student problem.”
Students are paying massive tuition, competing for grades, internships, jobs, med school, law school…
And schools still haven’t redesigned the system for the AI era.
If even professors admit cheating has become normalized, then the culture inside universities is already broken.
Microsoft just banned its own engineers from using AI.
The tool was literally costing MORE than the humans it was supposed to replace.
They lied to you about AI adoption and now the whole narrative is blowing up:
Microsoft gave thousands of engineers access to Claude Code six months ago and encouraged them to use it.
Engineers loved it and adoption exploded. But then the invoices arrived.
Token-based pricing means every query, every code review, every debugging session costs money. At scale across 100,000 engineers, the numbers became so large that Microsoft issued an internal order to cancel nearly all Claude Code licenses by end of June and force everyone onto their own cheaper tool instead.
The company that invested $5 billion in Anthropic just told its own people to stop using Anthropic's product because it costs too much.
Uber's story is even worse...
Their CTO Praveen Neppalli Naga told The Information that the budget he planned for the full year was "blown away already" by April.
Uber had rolled out Claude Code in December 2025. By March, 84% of their 5,000 engineers were using it with 70% of all committed code coming from AI systems.
Heavy users were burning $500 to $2,000 per month each. Naga himself spent $1,200 in a single two-hour demo session.
The company had even built internal leaderboards ranking engineers by how much AI they used. They literally gamified the spending and then ran out of money.
Now look at what Nvidia's own VP of applied deep learning Bryan Catanzaro said to Axios last month. Direct quote:
"For my team, the cost of compute is far beyond the costs of the employees."
This is a VP at the company that SELLS the chips saying that using AI is more expensive than paying humans.
Think about what this means for the entire AI narrative.
Every CEO on every earnings call for the past two years has said the same thing:
AI will make us more efficient, reduce headcount, and cut costs.
The stock market rewarded every company that said it.
Fired workers, stock goes up. Announced AI adoption, stock goes up.
But the actual companies deploying AI at scale are discovering the math doesn't work. The MORE employees use AI, the HIGHER the bill.
Goldman Sachs forecasts a 24x increase in token consumption by 2030 as companies adopt AI agents. Gartner just published a report showing that even though individual token prices will drop 90% by 2030, total enterprise AI costs will go UP because agents consume exponentially more tokens per task than basic tools.
Meta built an internal dashboard called "Claudeonomics" to track which employees use the most AI. Amazon started pushing engineers to "tokenmaxx," their internal term for consuming as many AI tokens as possible.
Both companies are spending hundreds of billions on AI infrastructure this year alone.
And Microsoft, the company that bet its entire future on AI, just told 100,000 engineers to stop using the tool they liked best because the per-token bills got out of control.
The companies building AI are telling investors it saves money. The companies using AI are finding out it costs more than the humans it was supposed to replace. And even the company that makes the chips just admitted it through its own VP.
This is the gap nobody on Wall Street is pricing in.
$725 billion in AI infrastructure spending this year across Big Tech. And the first companies to actually deploy these tools at scale are already pulling back because the economics don't work.
What do you think?