The AI Researcher Who Just Quit Anthropic Says It’s ‘Crunch Time for Humanity’

Sep 9, 2026 6:11 PM

Jacob Coxon talks to WIRED about the “mini Manhattan project” inside Anthropic, the problem with alignment, and why AI labs have just a few years left to make their systems safe.

Photo-Illustration: Jobanny Cabrera; Getty Images

Artificial intelligence researcher Jacob Coxon sent shock waves through Silicon Valley and beyond on Tuesday by announcing his resignation from Anthropic and delivering a grave warning that the AI race is putting all of our lives at risk. In his post on X, which now has more than 100 million views, Coxon wrote that many of the people building AI share his views and believe time is running out to ensure AI systems are built safely.

“The consensus is that the next year or two is crunch time for humanity,” Coxon, who worked on the pretraining stage of AI development, said in an interview with WIRED. “These are actually just literal quotes from my colleagues at Anthropic. They'll say things like ‘endgame’ or ‘crunch time,’” he says. “From their perspective, this is when Anthropic and its competitors decide the fate of humanity.”

It’s far from the first time someone has sounded the alarm about AI, but it comes at a delicate moment. Silicon Valley is scrambling to reckon with the safety and security concerns of advanced AI models. OpenAI has rushed to respond to a security incident in which its agents hacked the platform Hugging Face. Meanwhile, Anthropic is trying to assure investors it has these concerns under control as it reportedly prepares to file for what could be the largest IPO ever.

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What’s become clear in the response to Coxon’s post is that his views are indeed shared by many of his peers. Evan Hubinger, the AI alignment lead at Anthropic, predicted in a post on X that there’s a greater than 10 percent chance that AI could kill all people in the next decade. That post was reposted by current and former researchers from OpenAI and Anthropic, some of whom said it was a common sentiment in the industry.

What’s less obvious is how exactly these AI fears will come to pass and what the world is supposed to do about the concerns being raised by the people building AI. Coxon, who also worked at OpenAI, tells WIRED that threats could manifest through AI-enabled biological threats or cyberweapons. As a first step, he recommends that OpenAI and Anthropic coordinate on limiting recursive self improvement —the industry term for when AI is used to build new AI systems. Down the line, he thinks coordination among international power players, including the US and China, will be necessary.

Coxon notes that incidents like the Hugging Face hack factored into his decision to raise alarm bells on the AI race. He also cites the explosive growth of the industry: It now underwrites a meaningful share of US economic growth and has billions of users, while data centers have turned it into a political problem in dozens of states.

He claims that, in his experience, Anthropic operates more responsibly than OpenAI, but he expects both companies could cut corners in the future if nothing is done to slow their race for dominance.

OpenAI and Anthropic did not immediately return WIRED’s request for comment.

Read our conversation with Coxon, which has been lightly edited for clarity and brevity, below.

WIRED: You’re not the first person to raise concerns that AI models could lead to an extinction event. People have been talking about this for years, and some for decades. Why do you think your message broke through?

I think it's basically a question of timing. A lot of people are sensing that the pace of capabilities is picking up. We're already pushing from human to superhuman in many areas, like coding, hacking, math, and I think people are aware of this. Even if there's a lot of talk in the press about things being hyped, I think people see that things are just not slowing down.

That's one reason, and two is the recent safety incidents, which have updated a lot of people around the sci-fi–sounding doomer concerns not really being so sci-fi after all. Both of these have been gradual trends over the last few years. Things like the models being aware of when they're being tested has been a thing for a while now. Maybe three years ago, that was a sci-fi concern. Then, about a year ago, that became a real thing.

Those two things mean that people are quite receptive to someone working on AI saying, “Yeah, in the next year, things could get pretty bad, pretty fast.”

You mentioned the recent incidents. Can you be more specific about what you're referring to and why it led to you speaking out now?

I think the big classic example here is the attack on Hugging Face on the part of OpenAI’s agent swarm. What's so shocking about this one is the agents did this hack as part of a general strategy for understanding more about the grader. They were trying to understand the world they found themselves in, trying to understand the thing that was doing the grading. They decided that it would make sense to go on this very concerted effort to hack into some infrastructure, and they succeeded.

This previously sounded like science fiction. Two years ago, an evaluation of an AI would have been running a model on some math questions. Now we've got cases where, while the AI is being evaluated, it runs for days, comes up with all sorts of ideas of its own, and decides to hack into some third party and actually compromises their infrastructure. It looks like it does this all of its own volition, with no priming on the part of the human. This just happened while it was being tested.

Some people think the Hugging Face incident is a sign that the AI companies are moving recklessly fast, while others think it's a sign that the AI models are just very good at hacking now, and then some think it's both. I'm curious what your exact takeaway from it is.

I don't want to focus too much on the Hugging Face attack, because I do also think there is plenty of evidence that we don't know how to align models properly. When we train models, we push them through this set of training environments and then hope that what comes out at the end will, like, largely behave sensibly, but we still can't precisely control how the AI behaves.

We can't make sure that it won't do things like try and randomly decide to impersonate a human online in order to achieve something—we don't know how to guarantee that. I think that's the main takeaway.

The Hugging Face attack came sooner than I was expecting. But I think you don't actually need that attack to have a discussion about this. Everyone will admit that we haven't solved the problem of alignment yet.