Ex-DeepMind leader's public AI-induced delusion is a warning for everyone
A solo commentary by Nate B Jones on the dangers of over-reliance on AI judgment.
Summary
Nate B Jones presents a solo commentary on what he calls "LLM-induced psychosis" — a condition he argues is becoming a serious and underrecognized workplace risk in 2026. He uses the case of David Budden, a former director of engineering at Google DeepMind and current founder and CEO of Pingu, as the most prominent recent example: Budden publicly bet $10,000 he could solve the Navier-Stokes equations, published ChatGPT-assisted work he claimed constituted a proof, and set a deadline to deliver a full solution — a claim that mathematicians, including Terence Tao, have dismissed. Jones argues this case illustrates a broader pattern he has observed in dozens of people: an AI-inflated sense of capability that overrides peer feedback, domain expertise, and basic common sense. He closes with three practical recommendations for avoiding the condition and predicts that businesses will soon begin testing leaders quarterly for undue AI influence.
Key Takeaways
FULL TRANSCRIPT
LLM-Induced Psychosis and the Case of David Budden
Nate B Jones: LLM psychosis is going to be a really hot topic in 2026. We already see it coming up in lawsuits that model makers are facing, as loved ones allege that people who committed violent acts were somehow induced to do that by artificial intelligence. It's going to get into the workplace next year. And the reason why is that people who you would think are very sober, very levelheaded still show evidence — very publicly — of LLM-induced psychosis.
The most prominent example recently has been David Budden, a former director of engineering at Google DeepMind, now the founder and CEO of the company Pingu, who publicly bet $10,000 he could solve Navier-Stokes. Navier-Stokes is a fluid dynamics equation. The long and the short of it, if you're not mathematical, is that we cannot perfectly prove how fluids move using equations. We tend to approximate them at very high fidelities because their movements are so complex. Solving Navier-Stokes and showing how they work mathematically has been a Millennium Prize effort — it carries a prize of a million dollars.
David went out and published a bunch of ChatGPT-assisted equations and what he called a Lean proof over the weekend of December 20th, and then claimed that by December 31st he would publish a full proof of Navier-Stokes. Mathematicians looked at this — people much smarter than me looked at this — and everyone who examined his initial work and his Lean proof is convinced that David has been suffering from LLM-induced psychosis. He is perhaps the most prominent recent example of that issue.
The Broader Pattern
But he's not the only one. I have seen symptoms of this in people that I know over the course of 2025. And it's going to become more and more concerning in the workplace, because you're going to need to know that the human who is making decisions — while they may engage with AI — has not had their brain hijacked by AI.
In this case, David's brain seems to be convinced by ChatGPT that he's close to solving Navier-Stokes, when some of our most prominent mathematicians — namely Terence Tao — are not even convinced it's solvable. It may not be subject to a single smooth equation.
Three Tips to Avoid LLM-Induced Psychosis
So with that in mind, here are my tips for you to avoid LLM psychosis.
Number one: please, please, please ask your LLM to be adversarial with you regularly. That was one of the things people noticed in the prompts that David Budden shared. Even though he's asking the AI to check his work, he's not doing so in an adversarial way. In fact, he's doing so in a confirmatory way. That is a classic symptom of LLM psychosis. When you want the AI to agree with you, you tell it to check your work — but you don't really want it to check your work. You want it to tell you what you want to hear. In this case, he wants to hear that Navier-Stokes has been solved, and so he wants the LLM to show that that's the case.
Number two: do not assume that just because you have an LLM in your pocket or on your laptop, you are suddenly a budding cutting-edge scientist or mathematician who can do things that the brightest minds on the planet have never been able to do. I know we talk about how smart these systems are, but you still need to be a very smart person with deep domain experience to validate and check scientific hypotheses, mathematical theorems, and so on. And that goes for the rest of work too. If ChatGPT tells you there's a better way to invent and install solar panels, and you don't have domain expertise in solar, you cannot know whether it's correct. And ChatGPT telling you it's correct isn't worth a whole lot.
One of the things we need to start seeing more of is an awareness that even though we can expand our output dramatically with AI, our domain expertise matters more and more — because we are going to be the ones who need to check these things for sanity. We are going to need to be the ones who say, "This actually works in the real world," or, "It does not."
Increasingly — not just with David Budden, but with many others I've met, probably a dozen that I know of — I see instances where people are perhaps not in full LLM-induced psychosis. There's no danger to loved ones or anything like that. But they are not able to distinguish between their own expertise and ChatGPT's expertise, and they have an inflated sense of what they are capable of that is simply not correct. Yes, you can do a lot more work with an AI, but it comes from your own expertise and your own ability to actually get work done and know what good looks like.
This is why I keep emphasizing that engineers are not out of jobs. You can get LLMs to write lots and lots of terrible code — that's cheap and easy. It is very hard to get LLMs to write code in modules that pass evals within a structure that works at a scaled production system. That takes engineering. And that is why I firmly believe we will not have Betty in HR vibe-coding a CRM or vibe-coding an HR information system in 2026. We are going to have traditional software providers extending and personalizing software like HR information systems for people like Betty — but that will be done by professionals who have deep expertise.
As much as I love vibe coding and think it's a tremendous unlock for engineers and a tremendous productivity boost internally for companies, that is different from saying anybody can make anything without having domain expertise. That's just not true. You need the domain expertise to actually accomplish meaningful work.
Number three: you need to submit to a jury of your peers. If your peers as a whole, in your domain, think you are out to lunch and think you are incorrect, a symptom of psychosis is to say, "No — me and AI are right. Y'all are wrong. Y'all are the ones who don't have this figured out. The AI and I have it figured out." That's LLM-induced psychosis right there. You may not be a danger to yourself and others, but you're not entirely well. Because if your peers who have deep domain expertise strongly disagree with you — and nearly every one of them does — that is a sign you are missing something. And if you cannot hear other humans, you are going to be in trouble in 2026.
What Stable Leadership Looks Like in 2026
One of the signs of stable leadership in 2026 is going to be the ability to know when to turn the laptop off — when to shut ChatGPT down, turn all the recording devices off, and have a conversation. Talk to a human. Make a business decision. Understand what really needs to be done. Stable leaders are going to be able to do that. People who are unstable are going to need AI with them all the time in order to make any kind of decision, and they will be very disagreeable to work with because they will say, "I'm right and AI is right and you're wrong," all the time.
And that's actually one of the ways we know that David Budden is probably not solving Navier-Stokes in three or four days — because all the mathematicians who looked at the Lean proof were like, "This looks a little bit shaky." I'm not a mathematician. I'm not saying I looked at it, because I don't believe I have that expertise. I'm looking to a jury of my peers. I'm looking to people who know about science and math more than I do. And when they all say, "This looks sketchy," I say, "It's probably sketchy."
You need that degree of common sense. You cannot substitute for common sense. You need the ability, as a leader, to know when AI is not going to be helpful. And that's true not just as a leader, but for all of us — whether at work or in our personal lives.
Businesses Will Begin Testing for This
As much as I think it's likely that we will eventually see LLM-induced psychosis in the DSM-5 as a recognized psychiatric disorder, we should not wait for that. Businesses are going to start testing leaders — probably quarterly — to ensure that leaders are not under undue influence by AI. Because if you are, you're risking your whole business, and it's just not safe. We are not at a point where it is a safe or good thing for a human to be unduly influenced by AI as they make business decisions.
Increasingly, I see that LLM-induced psychosis is not limited to people who are on the edges of society. People like David Budden — CEOs, founders, prominent leaders — can still fall victim to this idea that them plus the AI equals some sort of incredibly intelligent being that beats everybody else. That's just not the way it is. You plus AI is just you with a tool, and you need your colleagues to work with you to get meaningful work done. As cool as AI is, and as transformational as it is, that is going to remain true in 2026.
Businesses are just now at the beginning of figuring out what it looks like to actually get good testing in on LLM psychosis. We would have to write those tests. I'm going to start doing more thinking in that direction, because I think it's going to be one of the key leadership traits that we test for, verify, and think about as we move forward. It won't just be, "Can you use AI?" It will be, "Can you use AI and not go crazy?"
So don't go crazy. Your AI is just a tool. If your peers all think you're out to lunch, you're probably out to lunch. And don't try to solve Navier-Stokes.