🦔GitHub Copilot switched to token-based billing this morning and users are already out of credits. Pro+ subscribers paying $39 a month are reporting 60% of their credits gone in two hours of normal use. One user lost 20% of their allowance from a single file review with no code changes. Another hit their monthly cap before the calendar even flipped to June.
Orgs with shared token pools have no way to see individual usage, so entire teams get cut off when one person runs a heavy prompt. Users are canceling and moving to Claude Code and Codex. GitHub community forums are on fire.
My Take
Flat-rate AI subscriptions were always subsidized. Everyone in the industry knew it. Today the subsidy ran out for a few million developers at once. The problem is a lot of companies already restructured around these tools. They cut headcount and told remaining engineers to lean on Copilot instead of building skills internally. Those companies now depend on a tool whose cost just became unpredictable and whose usefulness completely changes when you have to ration prompts to stay under budget.
The developers moving to Claude Code and Codex will hit the same wall eventually. Every AI provider faces the same unit economics. Anthropic filed its S-1 this morning, and the durability of its revenue depends on whether customers stick around once real pricing kicks in everywhere. If a $39 subscriber cancels after one day because the tool became unusable, multiply that across millions of seats and the churn risk becomes very real.
Today showed what happens when AI pricing meets reality. The companies that built their workflows around cheap tokens just discovered the tokens aren't cheap anymore and the people who knew how to do the work without them are already gone.
Hedgie🤗
🚨BREAKING: Two researchers from UPenn and Boston University just published a paper that should be uncomfortable reading for every CEO automating their workforce right now.
The argument is straightforward. Every company replacing workers with AI is also eliminating its own future customers. Laid off workers stop spending. Enough of them stop spending and nobody can afford to buy anything. The companies that fired everyone end up selling into an economy with no purchasing power left.
Every executive can see this. The math is not complicated. But here is why nobody stops.
If you do not automate, your competitor does. They cut costs, lower prices, take your market share, and you collapse anyway. So every company automates knowing it is collectively destructive because the alternative is dying alone while everyone else survives. The researchers proved this is a Prisoner's Dilemma playing out in real time.
The numbers are already moving. Block cut nearly half its 10,000 employees this year. Jack Dorsey said AI made those roles unnecessary and that within the next year the majority of companies will reach the same conclusion. Salesforce replaced 4,000 customer support agents with AI. Goldman Sachs deployed a coding tool that lets one engineer do the work of five. Over 100,000 tech workers were laid off in 2025 and AI was cited as the primary driver in more than half those cases. 80% of US workers hold jobs with tasks susceptible to AI automation.
The researchers tested every proposed solution. Universal basic income does not change a single company's incentive to automate. Capital income taxes adjust profit levels but not the per-task decision to replace a human. Collective bargaining cannot hold because automating is always the dominant strategy.
They also identified what they call a Red Queen effect. Better AI does not solve the problem, it accelerates it. Every company chases faster automation to gain market share over rivals but at the end everyone has automated equally, the gains cancel out, and the only thing left is more destroyed demand.
The one thing the math says could work is a Pigouvian automation tax. A per-task charge that forces companies to account for the demand they destroy each time they replace a worker.
The conclusion is that this is not a transfer of wealth from workers to owners. Both sides lose. Workers lose income. Companies lose customers. It is a deadweight loss with no market mechanism to stop it on its own.
(Link in the comment)
Manchester marathon yesterday..8th marathon and new PB but not exactly what I wanted. Was going well till 22 miles and then the cramp kicked in! Onwards and upwards. Marathons are not really my distance but I ain’t quitting.
@SandyofSuffolk This argument works unless you happen to have grown up in Lowestoft. A dead end town with no prospects and terrible transport links..what a genius plan!
My company rolled out AI tools 11 months ago. Since then, every task I do takes longer.
I am not allowed to say this out loud.
Not because there is a policy. There is no policy. There is something worse than a policy. There is enthusiasm.
There is a Slack channel called #ai-wins where people post screenshots of AI outputs with captions like "this just saved me an hour." There is a VP who opens every all-hands with "the companies that adopt fastest win." There is a Director who renamed his team from Operations to Intelligent Operations. There is a peer review question that now asks: "How have you leveraged AI tools to enhance your workflow this quarter?"
If the answer is "I haven't, because I was faster before," that is a career decision.
So I leverage.
Emails.
Before the tools, I wrote emails. This took the amount of time it takes to write an email. I did not measure it. Nobody measured it. The email got written and sent and it was fine.
Now I write the email. Then I highlight the text and click "Enhance with AI." The AI rewrites my email. It replaces "Can we meet Thursday?" with "I'd love to explore the possibility of finding a mutually convenient time to align on this." I read the rewrite. I delete the rewrite. I send my original email.
This takes 4 minutes instead of 2. The 2 extra minutes are the enhancement. I do this 11 times a day. That is 22 minutes I spend each day rejecting improvements to sentences that were already finished.
In #ai-wins I posted a screenshot of the rewrite. I did not post the part where I deleted it. 23 people reacted with the rocket emoji.
That is adoption.
Meetings.
We have an AI notetaker in every meeting now. It joins automatically. It records. It transcribes. It summarizes. After each meeting I receive a 3-paragraph summary of the meeting I just attended.
I read the summary. This takes 3 minutes. I was in the meeting. I know what happened. I am reading a machine's account of something I experienced firsthand. Sometimes the account is wrong. Last Tuesday it attributed a comment about Q3 revenue to me. My manager made that comment. I spent 4 minutes correcting the transcript.
Before the notetaker, I did not spend 7 minutes after each meeting correcting a robot's memory of something I personally witnessed. I attend 11 meetings a week. That is 77 minutes per week supervising a transcription nobody requested.
I mentioned this once. My manager said "think about the people who weren't in the meeting." The people who weren't in the meeting do not read the summaries. I checked. The read receipts show single-digit opens. The summaries exist not because they are useful but because they are there. I read them for the same reason.
Documents.
I write a weekly status update. Before the tools, this took 10 minutes. I typed what happened. I sent it. My manager skimmed it. The system worked.
Now I open the AI writing assistant. I give it my bullet points. It produces a draft. The draft says "Significant progress was achieved across multiple workstreams." I did not achieve significant progress across multiple workstreams. I updated a spreadsheet and sent 4 emails.
I rewrite the draft to say what actually happened. Then I run my rewrite through the grammar tool. It suggests I change "done" to "completed" and "next week" to "in the forthcoming period." I click Ignore 9 times. Then I send the version I would have written in 10 minutes. The process now takes 30.
I have been doing this every week for 11 months. I have added 20 minutes to a task that did not need 20 more minutes. I call this efficiency. I have been calling it efficiency for 11 months. That is what efficiency means now. It means the additional time you spend to arrive at the same outcome through a longer process. Nobody has questioned this definition. I have not offered it for review.
I kept a log once. 2 weeks. Every task, timed. Before-AI and after-AI. The after number was larger in every case. Every single one. Not by a little. The range was 40 to 200 percent.
I deleted the log.
I deleted it because it was a document that said, in plain numbers, that the AI tools make me slower. And a document like that has no place in a company where AI adoption is a strategic priority. I could not send it to my manager. He championed the rollout. I could not post it in #ai-wins. I could not raise it in a meeting because the notetaker would transcribe it and the summary would read "[Name] expressed concerns about AI tool efficacy" and that summary would be the first one anyone actually reads.
So I do what everyone does.
I use the tools. I spend the extra time. I post in #ai-wins. I write "leveraged AI to streamline weekly reporting" in my review and my manager gives me a 4 out of 5 for innovation. I have innovated nothing. I have added steps to processes that were already finished. I have made simple things longer and labeled the difference with words that used to mean something.
Every week in #ai-wins someone posts a screenshot. And 20 people react with the rocket emoji. And nobody posts the part where they deleted the output and did the task themselves. Nobody posts the revert. Nobody posts the before-and-after timer. Nobody will. Because "I was better at my job before the AI tools" is a sentence that cannot be said out loud in any company that has decided AI is the future.
Every company has decided AI is the future.
So we leverage. Quietly. Adding steps. Calling them optimization. Getting slightly less done, slightly more slowly, with slightly more steps, and reporting it as progress.
My yearly review is next month. There is a new section this year. "AI Impact Assessment." It asks me to quantify the hours saved by AI tools per week.
I will write a number. The number will be positive. It will not be true.
But the AI writing assistant will help me phrase it convincingly. That is the one thing it does well.
🤯NO ONE SAW THIS COMING…
Ethiopia’s Fotyen Tesfay runs 2:10:53 for the 2nd-fastest time women’s marathon time ever…in her marathon debut to win the Barcelona Marathon‼️
That’s 4:59/mile for 26.2 miles.💥
Watch how Mondo Duplantis cleared 6.31m for his 15th world pole vault record in Sweden 🚨
Duplantis cleared the mark at his own meeting and was mobbed by his other competitors afterwards 🇸🇪
Watch the full highlights on Eurovision Sport below 👇
https://t.co/1EgMIQfrfp