docs/PHASE_2_PLAN.md

🚀 PHASE 2 PLAN – ADVANCED INTELLIGENCE

Duration: 4-5 weeks (Dec 2025)
Owner: Autonomous MCP Team
Status: 🟡 In Progress

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🎯 Objectives

1. Unified GraphRAG – multi-hop reasoning across CMA + SRAG + PAL + ProjectMemory.
2. Role-Based Agent Teams – specialized agents coordinating via AutonomousTaskEngine.
3. StateGraphRouter – LangGraph-inspired orchestration of decision states.
4. PatternEvolutionEngine – evolutionary strategy engine with creative exploration.

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🗂️ Work Breakdown

Week 5-6 – GraphRAG + Agent Teams

Task	Description	Owner
Schema Design	Define graph schema (entities, relations, embeddings)	Memory Team
Graph Indexer	Build ingestion pipeline → GraphIndexer service	Memory Team
Reasoning Engine	Implement UnifiedGraphRAG.ts (multi-hop search, beam width config)	Intelligence Team
Agent Roles	Define Strategist, Researcher, Guardian, Synthesizer roles	Task Engine Team
Task Routing	Extend AutonomousTaskEngine to assign roles per task intent	Task Engine Team

Week 7-8 – State Router + Pattern Evolution

Task	Description	Owner
StateGraphRouter	Represent decision flow as nodes/edges with guard conditions	Orchestration
Memory Hooks	Each node can read/write UnifiedMemory snapshots	Memory Team
PatternEvolutionEngine	Genetic-like mutation of strategies, fitness via KPIs	Intelligence Team
Feedback Loop	Integrate PAL emotional signals into evolution fitness	PAL Team

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🔧 Technical Plan

• Graph Storage: Reuse SQLite (FTS + adjacency tables) for dev, abstract interface for Neo4j/Postgres later.
• Embeddings: Use existing SRAG embeddings; add relationship embeddings via averaged vectors.
• Multi-Hop Search: BFS + heuristic scoring, plus optional maxDepth, beamWidth config.
• Agent Roles: YAML definition in config/agentRoles.yml + runtime loader.
• StateGraphRouter: JSON/TS definition of nodes, each node points to handler + success/fail transitions.
• Pattern Evolution: Maintain population of strategies; evaluation uses telemetry + PAL signals; store in pattern_strategies table.

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✅ Deliverables

1. apps/backend/src/mcp/cognitive/UnifiedGraphRAG.ts
2. apps/backend/src/mcp/cognitive/StateGraphRouter.ts
3. apps/backend/src/mcp/cognitive/PatternEvolutionEngine.ts
4. Updates to AutonomousTaskEngine.ts for role assignments
5. Config docs: docs/PHASE_2_GUIDE.md

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📅 Milestones

Date	Milestone
Week 5 end	Graph schema + GraphRAG prototype
Week 6 end	Role-based agents live in TaskEngine
Week 7 end	StateGraphRouter orchestrating decisions
Week 8 end	PatternEvolutionEngine generating new strategies

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🚨 Risks & Mitigations

• Graph Complexity – enforce depth/beam limits; fallback to classical SRAG if query too broad.
• Agent Conflicts – Guardian role monitors conflicting outputs.
• Performance – nightly batch evaluations for PatternEvolution to avoid runtime spikes.

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📢 Next Actions

1. Build graph schema + ingestion helpers.
2. Scaffold UnifiedGraphRAG.ts.
3. Define role templates + update TaskEngine.
4. Design StateGraphRouter JSON schema.