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docs(04): create gap closure plans for memory and context management

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Phase 04: Memory & Context Management
- 3 gap closure plans to address verification issues
- 04-05: Personality learning integration (PersonalityAdaptation, MemoryManager integration, src/personality.py)
- 04-06: Vector Store missing methods (search_by_keyword, store_embeddings)
- 04-07: Context-aware search metadata integration (get_conversation_metadata)
- All gaps from verification report addressed
- Updated roadmap to reflect 7 total plans
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Mai Development
2026-01-28 12:08:47 -05:00
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.planning/ROADMAP.md
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@@ -51,11 +51,15 @@ Mai's development is organized into three major milestones, each delivering dist
- Distill long-term patterns into personality layers
- Proactively surface relevant context from memory
**Plans:** 4 plans in 3 waves
**Status:** 3 gap closure plans needed to complete integration
**Plans:** 7 plans in 4 waves
- [x] 04-01-PLAN.md — Storage foundation with SQLite and sqlite-vec
- [x] 04-02-PLAN.md — Semantic search and context-aware retrieval
- [x] 04-03-PLAN.md — Progressive compression and JSON archival
- [x] 04-04-PLAN.md — Personality learning and adaptive layers
- [ ] 04-05-PLAN.md — Personality learning integration gap closure
- [ ] 04-06-PLAN.md — Vector Store missing methods gap closure
- [ ] 04-07-PLAN.md — Context-aware search metadata gap closure
### Phase 5: Conversation Engine
- Multi-turn context preservation