Add human-led conversation learning loop

docs/product-and-safety.md

@@ -115,3 +115,10 @@ Read-only inspection, builds, tests, and documentation work do not grant any of
 Treat these as sensitive: `.env`, Reddit cookies, exported session JSON, Matrix access tokens, dashboard/agent tokens, the SQLite database, browser profiles, conversation text, usernames, received private media, operator exchange media, and logs that may contain request metadata.
 
 Never commit or reproduce them in documentation, fixtures, logs, issue text, or tool output. Prefer redacted structural evidence. Production backups contain account and private conversation data and need the same protection as the live volume.
+### Human-led conversation learning
+
+A received image is an outcome, not proof that the preceding AI action caused it. The learning loop therefore attributes every Matrix event before extracting an example and gives manual interventions their own credit classes: human-created, human-improved, and human-completed AI trajectories. Autonomous and recipient-initiated outcomes remain separate comparison cohorts.
+
+Only privacy-redacted decision context is retained as learning material. Media bytes, private attachment paths, raw prompts, usernames, URLs, email addresses, and phone numbers are not copied into examples. Exact Matrix event IDs are preferred; fingerprint or inferred histories are held for review according to `learning.minimumAttributionConfidence`.
+
+Examples mature only after the configured delay. Later declines, boundaries, or upsell classifications revoke the trajectory. An operator can explicitly include or exclude a trajectory in **Learning review**. Generation use is independently gated and defaults to capture-only shadow mode, so collecting evidence cannot silently change live replies.