Convex Self Heal

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Gated production self-healing loop

Sentry/Datadog/Vercel can go error→investigate→draft-PR, but they treat the backend as opaque and stop at the human merge gate with an unverified diff. Convex can do the step they can't: because the error rows live in the user's own deployment and the fix can be rehearsed on a preview of that deployment, the platform certifies the fix against real invariants before anyone reviews it. This capability is the composition capstone — it wires sentinel (capture) → the findings bus (diagnose) → the fixers (repair) → migrate-rehearse/tsc/probe (certify) → a human PR (decide) → deploy-guard (promote). The human keeps the merge button; the machine does everything up to and including proving the fix works.

Workflow

1. GUARD: deploy-guard — this loop reads prod and PROPOSES prod changes; classify + announce the deployment and get the standing consent for the loop's scope up front (what classes of fix it may auto-prepare vs must always defer). Never auto-merge; the human merge is the fixed boundary.
2. CAPTURE: require sentinel (prod errors in the user's own deployment, redacted at write time). If absent, offer to install it and stop — there is nothing to heal without capture.
3. TRIAGE a new/ recurring error: pull it via the official MCP (data/run-once-query over the sentinel table, or the monitor's prod_error event). Classify: transient (retry/ignore — do NOT open a PR for a one-off network blip), config (env/secret — hand to env, never guess a secret), or a code/schema defect (proceed).
4. ROOT-CAUSE on the findings bus: run the relevant audit pass on the implicated function — convex-insights (the failing requests + stacks), convex-advisor (if it's a read-limit/OCC cause), convex-reviewer/convex-authz (if it's a logic/authz defect). Produce a bus finding with evidence (the stack + the reproducing input) and a fixCapability. If root cause is unclear, STOP and report — a wrong fix is worse than an open error.
5. REPAIR via the finding's fixCapability (convex-authz, reviewer fixers, convex-expert for perf) on a branch — never on prod directly.
6. CERTIFY against the backend's own invariants BEFORE proposing (this is the differentiator — do not skip any that apply): (a) tsc --noEmit clean; (b) if the fix touches schema/data, run it through migrate-rehearse on a preview seeded with a prod snapshot — the schema-conformance gate must pass on real-shaped data; (c) reproduce-then-confirm-gone: replay the error's triggering input against the fixed code (a convex-test case or an MCP run on the preview) and assert the failure no longer occurs; (d) no-regression: the finding must be gone AND no new bus finding introduced on the touched function. A fix that fails any applicable certification is NOT proposed — it's reported as 'attempted, could not certify' with what failed.
7. PROPOSE, never merge: open a PR (or a diff for review) containing the fix, the certification evidence (tsc result, rehearsal outcome, the reproduced-then-gone assertion), the original error + finding, and the reversibility note. Label the change class. The human reviews and merges.
8. PROMOTE on merge via deploy-guard's prod consent; after deploy, re-check the sentinel table + logs (failures) to confirm that error signature stops recurring (do NOT use insights for this — it tracks only OCC/read-limit perf events, not arbitrary error signatures) — the loop is only closed when the error stops recurring in prod. If it recurs, reopen with the new evidence.
9. BOUND it: only classes the user pre-approved in step 1 are auto-prepared (default-safe set: validator fixes, missing-index adds, ownership-check adds, non-destructive backfills); anything destructive, security-sensitive beyond an added check, or ambiguous is always deferred to explicit human direction. Log every action to an append-only record so the loop is auditable.