Cheap checks first.
T0 is a deterministic checklist that runs in milliseconds — does the file parse? are the imports valid? is the manifest well-formed? A T0 failure aborts before a single T1 sandbox boots.
01 AI Product Studio
Two co-equal entry paths. Greenfield takes plain-language intent through PRD, stack, code, tests, and deploy. Brownfield imports your repo, audits architecture / security / quality, then enhances or renovates per your direction.
Every Studio build flows through eight agents. Validation runs at three tiers; the circuit breaker terminates non-converging retries. The trace is the artifact you ship alongside the code.
T0 is a deterministic checklist that runs in milliseconds — does the file parse? are the imports valid? is the manifest well-formed? A T0 failure aborts before a single T1 sandbox boots.
T1 runs pytest in a sandbox per feature. Failures get one or two more attempts — but only if the scorer trajectory is improving. Same-state retries cost nothing.
T2 sends every passing build past an adversarial AI reviewer with a counter-example prompt. If neither reviewer flags it, the build crosses the gate. If they disagree, a human is paged.
The cost meter checks every step against the pre-flight estimate. At 1.5× the estimate the circuit breaker trips — your tokens go where they compound, not where they spin.
No rewrite tax. The same agents that build greenfield also import an existing codebase, run a three-axis audit, and propose enhancements scoped to what you actually asked for.
.env.example (committed accidentally)· /search endpoint added · 1 PR · 84 LOC · 12 tests