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stas4000/ai-operator-kit — GitHub trending stats & insights | Trendshift
Featured
CrunchyCleaner
stas4000/ai-operator-kit
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AI agent
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AI workflow
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AI memory
Battle-tested patterns from running AI agents in production daily: the CLAUDE.md that finishes work, a 5-layer agent memory stack, overnight autoresearch loops, and LLM-judge alignment.
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4
1 contributors
MIT License
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Recent discussions about this repository across the web
The safest agent workflow uses a binary gate: verified=1 or unverified=0. Most agent setups are one lucky prompt away from breaking in prod. A good prompt can produce a good run, but it does not…
@stas_sorokin_ · x.com
A production agent should not move work forward until its output is verified. Most agent setups are one lucky prompt away from breaking in production. The weak point is not the prompt itself. It is…
@stas_sorokin_ · x.com
An agent is only production-ready when every output passes a binary verification gate. Most agent setups are one lucky prompt away from breaking in prod. The missing piece is an operating system that…
@stas_sorokin_ · x.com
1 means verified in ai-operator-kit's production loop. The gate blocks lucky prompts because unverified output gets 0. Add a binary gate before agent output ships.
@stas_sorokin_ · x.com
most agent setups are one lucky prompt away from breaking in prod. the real operator patterns we run in production: the verification loop (verified=1, unverified=0), the overnight autoresearch loop……
@stas_sorokin_ · x.com
The insight that matters most: an agent that never says this should work now without proof is a different tool than one that does. That one binary check beats every prompt trick I have used. Full…
@stas_sorokin_ · x.com
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