Jacob Coxon resigned from Anthropic on September 9, a few months after joining its pretraining team following roughly three years at OpenAI. In his exit thread he accused both employers of racing toward self-improving superintelligence while gambling with our lives. His sharpest point wasn’t about capabilities. The people building these systems, he wrote, earnestly believe AI could kill everyone by the end of the decade, and their private fears run hotter than their public statements. Within hours, Anthropic’s own alignment science lead replied by name to agree. Three days inside the thread, the replies, and the fallout left me somewhere uncomfortable. The extinction odds everyone is arguing about are the least important number in this story.
The number that should worry you more, though, is zero. That’s how much has changed at Anthropic or OpenAI since the warning landed. Both labs kept racing through the very news cycle carrying the warning.
Three researchers, three numbers that don’t reconcile
The replies turn one resignation into a pattern. Evan Hubinger, who leads alignment science at Anthropic, wrote that his colleagues really do believe AI could kill all humans, put his personal odds above 10% within the decade, and admitted the company has no plan to solve alignment for superintelligence, nor a clear path to one. Sit with that sentence. The safety lead of a frontier lab says the core problem is unsolved, and the schedule doesn’t change.
Samuel Marks, Anthropic’s scalable oversight lead, added the observation I keep returning to. The more senior the employee, the more concerned they are. Junior staff treat doom as an abstraction. The people closest to the training runs don’t. That inverts how institutional risk normally works, and it should unsettle you more than it unsettles them.
None of these numbers is an official position. Then Marcus Williams, a safety researcher at OpenAI, went further and put extinction at 70% within three years absent regulation or a slowdown, though he thinks a slowdown is genuinely possible. Geoffrey Hinton called 10% not unreasonable. Ten percent per decade and seventy percent per three years cannot both be calibrated forecasts, because there’s no shared method behind them. These are informed vibes with job titles attached, and the spread between them is itself the finding.
The parts that didn’t fit in a headline
I went looking for what came before the thread, and that’s where it gets darker. Coxon has described the internal vocabulary at these labs as already including terms like crunchtime and endgame for the next couple of years. The public posts weren’t a revelation. They were a private consensus losing containment.
The wave kept moving. Joe Benton left Anthropic’s safety team and Josh Engels left Google DeepMind within days, both citing safety concerns. Multiple safety researchers exiting multiple frontier labs in one week is a pattern, not a coincidence.
Here’s a contradiction nobody at Anthropic has reconciled. The same company publishing extinction warnings recently published economic scenarios for 2030 that assume rapid AI-driven growth. You can’t model a boom and an apocalypse from the same assumptions and call both rigorous.
The skepticism deserves airtime too. David Sacks flagged the timing of Coxon’s thread, the account’s thin posting history, and the speed of amplification by EA-linked accounts, and read it as coordinated rather than organic. Trump dismissed the warnings outright and pivoted to beating China. On Reddit, where I watched the r/cscareerquestions and r/singularity threads climb, sentiment split between “trust me bro” fatigue and people quietly recalculating whether an AI career still makes sense. It’s the same trust deficit we flagged in our piece on Meta’s AI agent trust problem, just scaled from shopping assistants to species-level stakes.
Underneath everything sits a prisoner’s dilemma with no exit. Unilateral slowdown hands the lead to rivals, including state actors, and nobody has proposed a way for labs to pause together and verify the pause. So everyone keeps racing. That’s not a conspiracy. It’s a trap, and everyone inside it knows it.
My take is that Hubinger’s admission is the part that should stick. Probabilities invite debate, but “we do not yet have a plan to solve alignment for superintelligence” invites accountability, and those are very different conversations. The test comes next. If these resignations convert into third-party evals, disclosure requirements, or a verifiable slowdown, the threads mattered. If they produce another wave of doomer resignations in October and another capability release in November, the warnings were never a call to action. They were the price of a clear conscience, paid so everyone could keep working.
Personally, I keep coming back to the seniority detail. The people with the most information are the most afraid, and they clock in anyway. If you need something lighter after all this, our piece on the return of alcohol has aged into unexpected dark comedy.
