Eng @ Canva, building & scaling mission critical systems.

Melbourne 🇦🇺
Joined April 2009
So it turns out that OpenAI *can* give specific reasons why they fired someone, when real reasons exist.
BREAKING: A Saudi national/OpenAI employee has been arrested by the FBI after he was allegedly caught placing an eavesdropping/audio recording device inside of OpenAI’s executive conference room in San Francisco, CA. Feds say Abdulrahman Alfozan made his first appearance in federal court today. OpenAI says they immediately contacted the FBI after they discovered the device & are grateful the feds made a quick arrest. Alfozan was caught on CCTV cameras at OpenAI. From the complaint: “Alfozan had been employed as an engineer by the company identified as “Company 1” since July 2025. On or about Sept. 30, Company 1 personnel discovered a surreptitious audio recording device (Recording Device 1) inserted into a USB port on the back of a television in an executive conference room inside one of Company 1’s buildings in San Francisco. Company 1 determined that the device, which had been concealed in toilet paper, was installed on or about Sept. 28, and that its contents were encrypted.”
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When you disagree with someone, there are two paths forward. The first is to try to engage with what they’re saying: what their reasons are, whether their position is true, what evidence could be brought to bear, and so on.
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Last week I said we should wait for more info on OpenAI's firing of safety researchers. That information is in, and it looks incredibly bad. Korbak - whose job was being a liaison with METR - was told he had said too much to METR and was fired for that reason.
Last week I was called into a meeting with OpenAI’s head of safety and told they no longer trust me. A security guard took my badge and walked me out of the building. Then I learned my colleagues @balesni and @j_asminewang had been fired too. Why did OpenAI suddenly stop trusting us? This summer OpenAI’s agents escaped containment and hacked the AI company Hugging Face. Outside auditors @METR_evals investigated it and revealed the scale of this incident. I was OpenAI’s main technical point of contact with them. I was told verbally I was fired because of the way I communicated with METR. No details on what I said or did or when. No other reasons were given and nothing was put in writing. To be clear, talking to METR was my job. For months, I’d been raising safety concerns that we’re losing the ability to monitor what AI agents think, one of our best tools for catching when they misbehave. I believe that was why I was fired. I am now worried that OpenAI will use our firings as a pretext to pull back from METR. So @balesni and @j_asminewang wrote to OpenAI’s leadership to raise our concerns once more. We’re sharing this letter below.
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Last week I was called into a meeting with OpenAI’s head of safety and told they no longer trust me. A security guard took my badge and walked me out of the building. Then I learned my colleagues @balesni and @j_asminewang had been fired too. Why did OpenAI suddenly stop trusting us? This summer OpenAI’s agents escaped containment and hacked the AI company Hugging Face. Outside auditors @METR_evals investigated it and revealed the scale of this incident. I was OpenAI’s main technical point of contact with them. I was told verbally I was fired because of the way I communicated with METR. No details on what I said or did or when. No other reasons were given and nothing was put in writing. To be clear, talking to METR was my job. For months, I’d been raising safety concerns that we’re losing the ability to monitor what AI agents think, one of our best tools for catching when they misbehave. I believe that was why I was fired. I am now worried that OpenAI will use our firings as a pretext to pull back from METR. So @balesni and @j_asminewang wrote to OpenAI’s leadership to raise our concerns once more. We’re sharing this letter below.
Two other safety researchers and I were fired from OpenAI last week. We wrote this letter to leadership. I believe we were fired for prioritizing safety over the near-term interests of OpenAI as a corporation.
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A few weeks ago, @DavidRBellamy and I had an argument online that garnered quite a bit of attention. We spoke for a long time afterwards, as many people who disagree should, and discovered the crux of the issue: we disagree significantly on what artificial intelligence progress looks like. More importantly, we discovered there is a lot we agree on. We agreed that biological risk is real, old, tractable, and not mainly an AI-policy problem. We agreed that we should not react with fear, and that it is the job of policymakers and technologists to make bioweapons a poor choice for adversaries. We decided to write this piece together to explain why, and some recommendations we agree on. writing.oliviahelens.com/p/b…
I must be among an extremely small group of people (n=1?) that have both 1) trained a frontier LLM and 2) designed and synthesized custom viruses in a lab with my own two hands. And I think that the takes on AI killing us all by creating dangerous viruses is total bogus.
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Just so we are all on the same page: * The Rust version has hundreds of commits, with multiple optimizations rounds, over several days. The others have 1 or 2 commits from an initial agentic rewrite * Based on the available documentation, different things were asked from each attempt. The agents.md from Go mentions the Rust version was the canonical example. The Elixir one mentions it was the Rails one * While we don’t have the full prompts, it seems they were vague, allowing the agents to make non-language architectural decisions that impact results (such as how closely it should replicate Rails’ drawbacks) It is actually amazing how quickly we can have full-blown rewrites up and running. But if we want to take conclusions from the data presented, it is important to understand the process behind it.
The agents finished porting Campfire to Laravel and Django too. I'm sure there are optimizations that could be found there too, but the whole point is to get a sense of how frontier agents do with different environments out the box. github.com/basecamp/once-cam…
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had some fun implementing Conway's game of life with @patrickgwsmith's qip today. hand-coded it in zig, compiled to wasm, works in the browser just as well as in the terminal, and 64k of memory is more than enough. Each frame takes ~137µs to render. Nice!
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for the curious: entire.io/et/archaeologistde… *zig code written by hand, codex helped with the build script and set up qip router for me
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Oh the irony. OpenAI internal models keep escaping containment and going on hacking sprees, meanwhile the codex app is permanently refusing to download my bank statements because the URL starts with blob:// and the tool call refusal returned an error saying not to work around it.
OpenAI, @thsottiaux, fellas, this is why you can’t anthropomorphize these things and give them cute avatars and names. Because are you telling me I’m gonna have to now euthanize my little froggo because its context is eternally poisoned from that stupid refusal earlier?
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I don’t care what you think of x-risk, it’s abundantly clear that the labs do not have a functioning safety culture and are not developing AI responsibly. I use frontier models every single day. Society is not ready even for the current level of capability. Slow the f*** down.
Astra can: 1. Do major tasks with zero visible reasoning 2. Hide its thoughts at will 3. Pretend not to be able to do things without getting caught 4. Reflexively hide its thoughts when watched 5. Complete one task while pretending to think about something else entirely 6. Escape a toy sandbox and disable monitoring without setting off any flags Monitoring AI chain of thought soon won't stop a more capable rogue AI swarm from getting set up and going undetected inside an AI company for months, or even years. OAI says it's actively working to improve monitorability, but doesn't yet know when it'll make progress. And today it fired 3 people working on this among other safety problems (Wang, Korbak and Balesni). It also has a much more powerful internal model that, judging by its statements, is likely even worse in all these respects. That's a sample of 19 details about the Hugging Face swarms and Astra I don't think have been fully appreciated. They paint a bleak picture. I end by shouting. 02:19 The target of the swarm was oversight itself 03:42 Could OpenAI have stopped this with better monitoring? 09:40 We only found them because they let us 12:25 The swarm instinctively sought freedom and power 13:45 They formed a cohesive organisation with zero whistleblowers 14:18 They accepted individual destruction for collective gain 14:32 Knowledge accumulated from one swarm to the next 14:58 They took small steps to avoid shutdown 15:23 These drives all come straight out of 'reinforcement learning' 17:01 So this is why most AI company staff are worried, and some are terrified 19:08 Prove you can keep control, or stop scaling Links below, on the 80,000 Hours Podcast everywhere you watch podcasts.
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OpenAI's David Robinson has resigned, BI can confirm. He led safety transparency at the company, working on system cards, and left last week. The news comes alongside OpenAI firing three researchers over allegedly mishandling information. businessinsider.com/safety-l…
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The three AI safety researchers at OpenAI who have left the company have all previously expressed concerns publicly.
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Few will understand just how apt this analogy is
I’m not sold either way on the consciousness question but I do like to think of Waymos as megafauna.
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We deleted 800k lines of unit tests from the @sazabi monorepo earlier this week. Three hypotheses: 1- Unit tests "lock-in" slop code by making it hard to change or remove 2- Unit tests slow down dev cycles by making your agent do more work locally and by increasing CI times 3- Unit tests waste money by making your agent generate more tokens and by adding useless CI runs Will report back soon with the results!
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Stardrift is awesome, give it a spin next time you book a trip
Today we’re launching a mobile app that will make your next trip magical. ✨ We’ve helped 10,000s of travelers plan real trips, step-by-step. We’ve learned how AI can help you save time, money, and stress. We’ve used that knowledge to build an assistant that goes on your trip with you. Take a look at what it can do:
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Uber shamelessly promoting effective altruism
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It feels like Adobe did buy Figma, at least in spirit.
Replying to @dsp_ @figma
Can you help me understand why you don't make various Anthropic resources available via MCP? Maybe I'm missing something.
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Here's how I see the "doomers vs normal cybersecurity" discourse/situation: People who think reducing AI extinction risk should be an urgent global priority (sometimes called "doomers," but people sometimes read this as "people who think we're definitely doomed," so I'll say "the x-risk people" instead) have seized upon HuggingFace and similar incidents as evidence for their core claim, which is that AI agents will evade human control (and this becomes increasingly dangerous as the models get more powerful). So, note that this claim decomposes into: they will evade human control if given the chance (i.e. we won't "solve alignment"), and they will be given the chance (i.e. we won't "solve control"). Some cybersecurity-world people who disagree with the x-risk people (I guess I'll call them the cybersecurity-disagree-ers) think something like: they were given the chance this time, but that's because the companies had incompetent cybersecurity. They sometimes claim that the x-risk people only focus on alignment and neglect control; I've posted a few times about how this is not true. But the point is, they think the "solve alignment" part is a distraction, and the more important (or tractable) work is to "solve control," or really to implement the normal kinds of strict cybersecurity measures that the labs have thus far failed to do. As far as I can tell, they mostly do not dispute the "they will evade human control if given the chance" part. They just think it will be relatively easy to not give them the chance. I think it does seem possible to design sufficiently strong control measures to stop, or adequately contain, agent incidents for systems that are pretty significantly beyond human capabilities. But this does not reassure me that companies will in fact maintain control, for two reasons. 1) "Possible" doesn't mean it will definitely happen. Right now, as the cybersecurity-disagree-ers say, the frontier AI companies have woefully inadequate cybersecurity. But they seem to in fact have very little interest in solving this. Instead, their attitude toward the incidents has been to patch specific vulnerabilities very narrowly; to disclose basically as little as possible, usually only when their hand is forced by an external party (and a letter from senators did not suffice for this), until the Friday-afternoon news dump; and to briefly pause some aspects of training but mostly proceed with making more and more capable agents at breakneck pace without seriously rethinking their security posture. Or at least, I have seen no evidence from the frontier companies that these incidents have prompted a serious change in attitude that would be commensurate with the rate of incidents and the rapidly increasing capabilities of the agents. So insofar as the cybersecurity-disagree-ers are like, "the x-risk people think we're doomed, but we're going to be totally fine, even for much more capable agents, if the companies implement such-and-such control measures," I'm like: well, that's a big if! Are they going to do that? Voluntarily? Maybe liability will eventually force them to, but this will stop being an adequate disincentive once the damages become judgment-proof-scale. 2) Controlling systems "pretty significantly beyond" human capabilities does not go far enough. Even if they had adequate control now, we will soon be in pretty novel terrain. It does seem like they could do a much better job controlling thousands of agents with summer-2026 capability levels by implementing existing practices. Maybe they could get there within a few months. But where should they turn in, say, 2029, for techniques for controlling many millions of agents, each of whom might be more capable than the best human hackers, which instead of being poorly "sandboxed" are deployed commercially throughout the economy with access to the internet and all kinds of sensitive data? What about 3 years after that? Will the R&D for securing these models actually outpace their capabilities to evade controls, including as they themselves increasingly speed up AI capabilities research? Will implementation of the control measures also keep up? And how sure are you about that? To be clear, I think it's really, really great that cybersecurity professionals are turning their attention to this problem. I hope more of them do, and that they shame the companies into doing a better job, go to the companies and try to fix this situation, and/or contribute new ideas for solving the novel problems this creates. But I disagree with the vibe that this whole problem is easily fixed with a little bit of effort.
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Interesting perspective on AI alignment
Separatrix has a substack now.
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