#OPUS48#RANOUTOFTOKENS Used opus 4.8 at default of high for 18 mins "You're now past your plan's included usage. Your session limit resets at 12:00 PM." Anthropic give us a break please
A company gave every employee unlimited access to Claude.
Set zero spending limits.
Got a $500 million bill. In one month.
Meanwhile Meta made token usage a leaderboard.
Low score meant getting fired.
So engineers left AI agents running all day doing nothing.
Just to keep their jobs.
AI was supposed to replace the humans.
Instead the humans figured out how to game the AI metrics.
Nobody is getting replaced. Everybody is just bleeding money.
$MSFT Microsoft To Release New Coding Model Next Week - Information #AI#AGI#TASKBASEDMODELS https://t.co/XACRQE5uqJ via @Street_Insider Microsoft To Release New Coding Model Next Week - Information
Microsoft To Announce New Models Of Various Sizes
Microsoft To Debut Models That Specialize In Tasks
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?
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Personal update: I've joined Anthropic. I think the next few years at the frontier of LLMs will be especially formative. I am very excited to join the team here and get back to R&D. I remain deeply passionate about education and plan to resume my work on it in time.
If you are running a consulting business and you are deploying Anthropic or OpenAI directly into your organization (I’m looking at you PwC and Accenture) you are letting the fox into the hen house.
OpenAI and Anthropic are openly funding and starting competitors to you while also using your usage to drive more success for them.
This is not a failure on their part but a failure on your part.
Consulting businesses that understand this are adopting a control plane that allows them to arbitrate where tokens go and who generates tokens for them.
Controlling the tokens is controlling the spice (Dune).
This was a key pillar of 8090’s global partnership with EY and they key feature of our Software Factory. We control token generation and can direct them to any model provider.
We are close to another global partnership and will announce it soon.
These organizations refuse to accept the disruption standing still or, even worse, by adopting and accelerating the companies who want to disrupt them.