AI Coding's Real Bottleneck Is Repository Execution Trust
Overview For a while, the central question in AI coding felt obvious: Can the model generate good code? That is still important, but it is no longer t…
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From Execution Logs to Governance Verdicts in Ota
Overview Most execution tooling still makes operators do too much reconstruction work. You get: command output step logs maybe a receipt maybe a CI su…
Pressure-testing Ota on Cal.diy: native, quickstart, and Docker runtime truth in one contract
Overview Cal.diy was useful because it forced one contract to describe several legitimate runtime truths at once: a native contributor development loo…
AGENTS.md Is Not Enough for Safe AI Agent Execution
Overview AGENTS.md is useful. It gives AI coding agents a place to find repo-specific guidance: how to behave what conventions matter what areas need …
Why Developer Onboarding Should Be Contract-First
Overview Most developer onboarding is still operationally weak. A new engineer clones a repo, opens the README, installs dependencies, runs the obviou…
Pressure-testing Ota on Discourse: repo-wrapper truth matters more than a passing bundle command
Overview Discourse turned out to be a good pressure repo for a narrow but important reason: the difference between bundle existing and the repo's real…
The Ota Skill for AI Agents
Overview We built the Ota skill because too much "AI repo automation" is still fake confidence. An agent clones a repo, finds a plausible command, edi…