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?
A surfer experienced seconds of extreme tension when, upon taking on a huge wave, she was unexpectedly in the middle of a wild scene: a seal fled desperately while being chased by a orca.😱
BREAKING: David @friedberg says "California is functionally bankrupt"
"People don't realize how screwed California is, & I worry that if California falls, so does the union.
"$250 billion to $1 trillion short."
"This is because for California to get rescued would be a big cost to red states, & I think it creates in the years ahead a lot of tension."
"California's functional bankruptcy is a major risk to the country. & I think we need to figure out what we can change to fix it."
How we got here:
"California has a public pension system, & that public pension system retirees have paid into it & they get some benefits out, & the amount that they're owed back out is somewhere between $250 billion - $1 trillion dollars more than has been paid in.
$250 billion to $1 trillion short.
If it was the federal government, it would be like, okay, we'll just print more money. California doesn't have the ability to print money, so California has to pay this out, and you can't restructure retirement benefits.
There is a Supreme Court case in California that said that once an employee has been offered retirement benefits, even if they're currently an employee, you can never restructure their retirement benefits.
It has to stay forever, and the state cannot declare bankruptcy. There's no way for the state to functionally declare bankruptcy. There's no law to allow it. No state has ever declared bankruptcy, and the retirement benefits sit senior to the bonds in California.
So you have to pay out the retirement benefits before you pay out all the bond holders that have loaned California the money that they use to run all their programs and services."
Hill & Valley Forum 2026 (@HillValleyForum)
🚨 HOLY CRAP! Scott Bessent just PUMMELED Gavin Newsom in Davos
"He's here this week with his billionaire sugar daddy, Alex Soros!" 🔥
"I think it's very, very ironic that Newsom — who strikes me as Patrick Bateman meets Sparkle Beach Ben — may be the only Californian who knows less about economics than Kamala Harris!"
BOOM!
Marc Andreessen says social media is an x-ray machine, revealing what legacy media used to keep hidden.
"And so the world that you experience with social media as a consumer is completely different."
We’ve moved from mediated trust to direct scrutiny.
The filter is gone. Everything’s visible now.
.@pmarca and @jaltma on underestimating market size and how tech evolved from tools to total transformation.
“It turns out some of these markets just turned out to be much larger than people think… like one of the things that's been hardest for us to do is to do market sizing and sometimes we overestimate market size… but more often it’s the other way.”