dreaming

# Dreaming. Automated Memory Consolidation Three-phase background process that turns raw session data into durable long-term knowledge. Like sleep for AI. consolidates, scores, promotes, and prunes memory. ## When to Run - Scheduled: daily at 03:00 local - Manual: `/dream` or "consolidate memory" ## Phase 1. LIGHT (Ingest + Deduplicate) Read all inputs: - `logs/session.jsonl`: last 24h of session events - `memory/*.json`: all persona memory files - The PROJECT memory/ tree (`memory/`: MEMORY.md, Context/, Learnings.md, user-model.md, etc.) AND the harness auto-memory tree (read-only). NOTE: dreaming WRITES only to the project memory/ tree, never under the harness home dir (see Phase 3 — the cron-tier session hangs on the CLI's home-dir self-edit guard). Actions: 1. Extract memory candidates from session logs (decisions, preferences, context, learnings) 2. Deduplicate against existing memory entries (fuzzy match on content) 3. Stage unique candidates with metadata: source, timestamp, category 4. Count recall traces. how many times was this info referenced in sessions? Output: staged candidates list (in-memory, not written yet) ## Phase 2. REM (Pattern Recognition + Reflection) Analyze staged candidates for: 1. **Thematic clusters**: group related memories (e.g. "the operator prefers X" + "the operator said do Y" = same theme) 2. **Contradictions**: flag memories that conflict with each other (newer wins) 3. **Staleness**: memories referencing dates/states that have pas...