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Get Out of the Model's Way — Kevin Hou, Google DeepMind

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AI Engineer
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AI Engineer
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Key takeaways · AI-distilled
  • Hou says Antigravity built an OS kernel that runs Doom from scratch using 93 subagents over 12 hours, about 2 billion and under $1,000.
  • His product principle is to get out of the model's way, so the tool improves every time the model does; he also recounts hard calls such as removing chat from Windsurf.
  • Antigravity 2.0's building blocks are dynamic teams led by Gemini 3.5 Flash via /teamwork, sidecars (a plugin protocol letting agents react to webhooks, cron jobs and messages) and generative UI.
  • He says DeepMind researchers automated about 90% of analysis by running 100 hypothesis agents in parallel.
Terms in this piece · Glossary
  • multi-agent — Using several AI agents on one problem — splitting work in parallel, checking each other, or filling different roles like planner and reviewer.
  • AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
  • token — The chunk of text a model reads and writes in — roughly three-quarters of a word — and the unit AI usage is billed in.
  • eval — A repeatable test for AI quality — a set of tasks plus scoring — used the way software teams use test suites, because model output is too variable to judge by eyeballing.
Why it matters

Shares specific figures behind an team building an OS kernel from scratch, and introduces Antigravity's dynamic subagent teams and sidecar protocol for webhook/cron-triggered agent work.

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