Hierarchical Multi-Agent State Management

Technical Implementation

State Machine Architecture

Centralized STATE.json audit trail ensuring 100% replayability of agent decisions. Every decision is timestamped, indexed by agent, and committed to immutable storage (Git).

• Immutable Decision Log: 2,170+ lines of documented decisions with full context trails
• Replay Capability: Reproduce any decision state at any timestamp
• Audit Trail: Git-backed versioning for compliance and forensics
• Performance Tracking: Token usage, latency, and accuracy metrics per agent

Concurrency & Parallel Execution

ThreadPoolExecutor implementation for parallel agent execution (Search + Vision + Calculator simultaneously).

• Tier 1 Parallel: All Executive agents run concurrently (ApplicationArchitect, RevenuePlanner, TechLead)
• Tier 2 Parallel: All Specialist agents dispatch simultaneously for their assigned tasks
• Latency Reduction: 60% faster execution vs. sequential agent chains
• Resource Efficiency: Optimal thread pooling prevents API rate limit collisions

Conflict Resolution & Auditing

Dedicated "Auditor" agents that review output discrepancies between swarms before committing to the database.

• Cross-Validation: Multiple agents evaluate the same input; discrepancies trigger escalation
• Confidence Scoring: Outputs ranked by agreement level (100% consensus = highest trust)
• Automated Escalation: Low-confidence results routed to Tier 1 for human review
• Decision Versioning: Track evolution of decisions across multiple reasoning passes

Wrecking Crew Execution Logs

Real orchestration runs from the RUNE Agent Swarm (December 2025):

Parallel Model Dispatch (Tier 1)

• GPT-4o (Architect): System architecture, code structure, component design
• DeepSeek R1 (Philosopher): Strategic reasoning, edge case analysis, philosophical framing
• Gemini 1.5 Pro (Visionary): Creative solutions, multi-modal integration, UX innovation
• Llama 70B (Engineer): Performance optimization, implementation details, error handling

R&D Hypothesis Tracking

• H-001: Multi-agent specialization produces higher quality than single generalist (ONGOING)
• H-002: Context persists across sessions via structured handover docs (VALIDATED)
• H-004: Self-aware AI creates better immersion in games (PROTOTYPE EXISTS)
• H-005: Multi-model synthesis produces better results with proper weighting (ONGOING)