Anthropic MTS. Previously founded @alpine4work, frontend infra @meta, early @airtable, and OSS contributor

NYC
Joined November 2013
My identity pre-2023 was wrapped in the fact that I enjoyed writing code and that I was really good at it So it’s surprising to me that I don’t miss writing code…at all I think that’s because AI rewards curiosity. I got good at writing code because I was first curious about how to build a nice looking website Working with frontier models, every prompt there’s something just beyond my current understanding and all it takes is one more prompt to learn more I’m creating more than I ever have before while I’m learning more than I ever have before! It’s wonderful Stay curious
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A recent Opus 5.5 project of mine was using @bendlang to generate realistic looking worlds applying: • Plate tectonics • Climate modeling • Formal verification • Projection geometry I learned a lot!
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After 4 years working on Alpine, we’re shutting it down and I’m joining Anthropic. All of Alpine’s code is open sourced and lifetime access customers were refunded. I started working on Alpine in 2022, before the launch of ChatGPT. Everything about the software industry…and the world…has changed since then. Alpine was conceived, designed, and engineered for a world where the only kind of collaboration is human-to-human. If I were to start over and design Alpine today: 1) I’m sure I’d make some very different decisions, 2) I’m not confident I’d make the right decisions! I haven’t experienced what it’s like to work at a large company with agents. I’ve observed first-hand how the rise of agents has changed my startup, but I haven’t seen how they impact companies with hundreds of people. My product design intuitions are influenced by my personal experience, so designing a productivity tool without understanding how AI has fundamentally changed the productivity substrate of our age feels foolish. As with many others, over this year I’ve observed the risks posed by AI become much more salient. I remember meeting EAs pre-ChatGPT and learning about x-risk and their steep AI safety investments, at the time it all felt like sci-fi (plausible, but far out)…now it’s reality. I’m excited to join Anthropic to help the world make the AI transition safely. I’m deeply grateful to everyone who saw Alpine’s vision. I enjoyed every minute working on Alpine thanks to our customers, investors, and employees. I’m sorry it didn’t work out, times are weird.
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I’ve replaced emdashes in my writing…with ellipsis Used to be a big emdash user but whereas before emdashes were a sign of careful narrative construction…now they’re a sign you offloaded your thinking …but an ellispsis gives a similar pause (and you can use it in new ways) Like at the end of a sentence to invite the reader to continue on… …or at the beginning of a sentence to pick back up where you left off And you can still…albeit in a slightly more awkward way…use the ellipsis for asides within a sentence Can’t wait for LLMs to adopt this quirk and I lose another favorite punctuation mark
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Whoa. This seems well poised to help with two big problems: 1. Fraud detection 2. Model alignment confirmation Instead of METR using ChatGPT to understand if ChatGPT was misaligned during the HuggingFace hack now you have a cheap *independent* (???) model with confidence scores you can run against every agent swarm trace You could run this thing as a cheaper classifier for dangerous behaviors like bioweapon development too For fraud, imagine sending millions of logs and it can tell you which ones are fraudulent very fast Disclaimer: I haven’t used the model and don’t understand how it works, just evaluating based on the company’s own claims. If the claims hold up…seems cool
After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x cheaper (w/ output tokens free) • Frontier composable intelligence optimized for decisions AFAICT the shortest path to AI-based economic revolution
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Great point
This is cool, but if your output domain is known in advance, why not just train a model to produce logprobs over enums?
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More of this! What a rich, information dense way to learn about other places
Okay but there are three kinds of NC rich
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Another one that taught me a lot
Bay Area starter pack - mom edition
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The wayfinder skill by @mattpocockuk is great At first I was skeptical, I’ve managed big projects just fine by myself But what’s nice about this skill is I never have the blank canvas problem. There’s always something to sharpen my ideas against There’s more room for taste expression because the “default” decision is already there in front of you. You can either accept and move on or refine Collaborative wayfinding sessions are also a great way to build alignment 10/10, great skill
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uh oh, i forgot how to write code
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Who’s right? When exploring an idea with an LLM my cofounder will avoid saying what he thinks to avoid a “you’re absolutely right,” he fears the agent will stop exploring other options I’ve found that agents will push back when I’m wrong so I’m not afraid to say what I think
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With coding agents instead of saying: "Change X to Y" …I unconsciously say: "What do you think about changing X to Y?" I'm used to phrasing suggestions as a question in code review with humans to be polite. Now changing code is cheap, I should tell the agent to do the thing
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Most of the time it does the thing I ask, sometimes it says "good idea, I'd make this change" and then I have to tell it to go actually make the change
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Some amusing light mode bugs this morning in Codex. Am I the only light mode Codex user? @thsottiaux
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I still experience flow but it’s different! It’s more hectic and chunky, less smooth. But I’m still absolutely engrossed and it’s hard to tear my attention away. I only reach flow state at 3+ productive agent threads running. Below that there’s too much waiting.
It’s a weird complaint to have but with AI agents, that “flow state” during coding is gone (because the coding itself is gone.) Every time I talk with a dev about work now vs before, it seems to come up, like today with a former colleague. Are we over-glorifying it (I mean it wasn’t all roses, it was also frustration) or is it something important / relevant they we had but now don’t really have?
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I've been thinking a lot about what "AI-native productivity suite" actually means I think everyone chasing this has been approaching it from the wrong angle No one has asked the question "what does the AI want?" and designed for that first and foremost
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Most repeatable processes in Google Docs are still: copy the old doc → rename it → manually update everything Alpine templates let you use lightweight {{variables}} throughout a document. Enter values once and every reference updates automatically
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