AI Agents, Computer Use & DevTools | Ex @playwrightweb Core Engineer | Previously Amazon AGI + Microsoft | SF

San Francisco, CA
Joined November 2011
Never trust a verbal job offer. I recently had one from a frontier AI lab. → Reference checks came back positive → Visa work started and was moving forward Two weeks later I got an SMS: "We are not able to move forward" while waiting for the written offer. The reason given was that they’re no longer hiring seniors and are focusing on juniors and new grads instead. 🤯 Is that the real reason? Who knows. I liked their product. I was hyped. Moving on and talking to more companies. Especially curious about computer use, browser use, RL environments, and coding agents right now. – at San Francisco, CA
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Congrats on the launch! 🚀
Introducing Expand Fetch, a new way to scrape and crawl the web. Your agent has never seen the web. No wonder it gets basic questions wrong. Traditional Markdown APIs lose critical details. So we trained two System one models to change that: Iris, a vision model that sees pages like you do, preserving tables, icons, and layouts. X-Ray, a JSON model that uncovers the hidden data behind every page. Every fetch also comes with a Wayback Machine. Every line links back to its source, so you can verify exactly what your agent saw. Three products. One API. On our benchmark of 1,094 questions across 326 challenging web pages, agents using Expand got 74% right. The next best API got 55%. Available today at $1 per 1,000 fetches. Try it at expand.ai
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A friend has his YC launch tomorrow - I’m so excited for him… Agents 🔎 Web
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Time for another Rust rewrite and making it easy for agents to debug GitHub Actions 🙌 – at San Francisco, CA
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Monthly reminder: myaccount.google.com/linkeda… Make sure to review and remove unused providers which are connected to your Google/Notion etc. accounts.
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I benchmarked 4 AI agent “cloud computers” with the same open script: Grok, Instinct, Muse, OpenAI. Multi-core CPU: Grok ≈ OpenAI (~2.5k ops/s). Instinct/Muse are tiny 2-vCPU cages. “Fastest disk” is a trap — some put /tmp on RAM 🤯 Same script, totally different machines: gist.github.com/mxschmitt/57… – at San Francisco, CA
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Quick stack notes from the dumps: - Grok - fat KVM overlay, ~8 vCPU / 16 GiB, user box - Instinct - ~2 GiB cage, real ext4 root, feels Firecracker-class - Muse - runs as root, /tmp = tmpfs - OpenAI - Kata + tmpfs root, all caps dropped, “disk” win is RAM -> Agent sandboxes are still very un-standardized. – at San Francisco, CA
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The engineering efforts big labs put into their Desktop harnesses definitely shows. I was surprised how good ChatGPT Desktop and Claude Desktop is coming from their terminal or cloud only experiences. ChatGPT work/normal mode is insanely confusing tho. :/
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When does Cursor / Grok Bot ship a real Kanban board for agents? Drop in a prompt, split it up in sub-problems, get a dependency tree. Cards show what’s in flight. Each one is a GitHub or Origin PR as an outcome. Parallel by default. Conflicts only when two tasks actually touch the same file (try to avoid). Communication can still happen between them to share investigations and outcomes. PR as an outcome is no must. Or am I missing something?
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Talking to a lot of companies lately and it's either a hard push toward open source models / inference / training or huge skepticism of the whole thing. 📣 Both camps are loud. They scream: - Open source will take over - We need to build the best cloud agents platform - I already have the best cloud agents platform - Frontier wins anyway That's what most of us talk about. In practice Grok Bot / Muse is the thing that matters right now. A safe consumer product with integrations: - How does my dad move from Codex (yes he codes VBA in Microsoft Excel with it :D) to actually using an agent - Let the agent run his email inbox, iMessage, WhatsApp, socials - How do you sync that at scale, across a lot of PRs (merge conflicts) for SWEs - How do you make deploy less painful. Still hard. Credentials, databases, no CLI, payments, buying a domain - Who do we trust - and how do we make sure it's actually secure? - How does a human tell when something is off. Chain of thought?! The fine line of "hey human, I'm actually not sure" vs "I like to ask for everything" e.g. permission approvals - When is Cerebras inference (or faster) available for everyone Excited for what's next. A lot more coming. Girlfriend said nobody will read this anyway. Reply with a panda emoji if you did.
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I cannot wait for a world where we get 10x/100x faster inference and we don't need to context switch anymore.
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I searched "chatgpt" on Bing. Five ads load before the real ChatGPT. The first is Microsoft advertising Copilot (ok fine). The next four are strangers bidding on OpenAI's name - one registered 4 months ago, one flagged as adware. chatgpt.com is 6th on the page. After scrolling 960 pixels... I'm worried about my parents who navigate the web and use Bing (Windows/Edge default) by default.
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Who's buying those slots: - ask-chat.ai - registered May 2026, impersonates OpenAI, trial converts to recurring charges - use.ai - real service, but the trial quietly becomes $29.99/mo - popsilla.com - adware, 85k+ infected machines - chatbotapp.ai - clones the ChatGPT UI ChatGPT is one example - out of many.
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I wonder if @ChatGPT or @bing can do something there - its been like this for a long time and this tactic seems to be popular about websites like this.
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This reads like science fiction. Agents: - rewrote /etc/hosts to bypass DNS - found an old GET-writable PHP forum - used private SSH tunnels - turned scrapers into tools - gamed runtime after learning they die when done Toddlers vs chess grandmasters. collusion.wiki
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Muse/Grok Bot has been an important part of my „agentic“ job hunt pipeline: - Central database in Notion - Monitor email inbox / Calendar/ X DMs / LinkedIn - Meeting prep documents for each call - Transcribed meetings in Notion - Deep Research sometimes via Claude/ChatGPT – at Cupertino, CA
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Just got to the meetup for Grok Bot @bot for Engineers in SF. Curious how this goes.
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@lingxi‘s Team: highly specialized team members: - Communicate mostly via chief of staff - Team members do get created and onboarded via others existing team members - Agent to Agent communication is the powerful magic - Useful plugins are already available
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To wrap up: - Treat bots like interns - Prevent human in the loop - Have verification loop -> Playwright or Computer Use screenshots
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