continuous-learning

# Continuous learning — the feedback loop of the harness This is the engine that makes the system get better every time it is wrong. When something broke, got corrected, surprised you, or simply taught the workspace something, your job is to **catch that lesson and route it back into the durable apparatus so the same mistake cannot recur**. One premise is load-bearing: **a lesson that lives only in chat is gone at the next compaction.** Verbal reflection only changes future behaviour when it is persisted to memory the agent actually reads next time (this is the Reflexion mechanism — self-reflection written to durable memory, not held in the conversation). In this harness, "memory" is a concrete set of surfaces: a `SKILL.md` body, `02-DOCS/wiki/harness/decisions.md`, `02-DOCS/wiki/harness/user-profile.md`, a root `CLAUDE.md` rule, or a `verify.sh` check. **Chat is not memory.** A lesson is "captured" only when it has landed in one of those. Read `02-DOCS/wiki/harness/user-profile.md` for the accompaniment dial before you narrate. It governs narration only — the capture loop runs identically at every level. ## Boundaries | Situation | Owner | Why | |---|---|---| | "We chose Postgres over Mongo, here's the why + the rejected options" | `../decision-records/SKILL.md` | forward choice with alternatives; a choice is not a lesson from a mistake | | "The migration failed because Postgres rejects NULL on the PK — never assume that again" | `continuous-learning` | backward lesson ...