hive-mind-advanced

Coordinate distributed agent teams using queen-led hierarchical orchestration with specialized workers like researchers, coders, and analysts. The Hive Mind automates task distribution, consensus decision-making, and shared memory management so agents operate as a cohesive unit without manual oversight.

Implement Byzantine consensus mechanisms that enable robust collective decision-making even when some agents fail or provide faulty data. The Hive Mind supports majority voting, weighted consensus, and Byzantine fault tolerance across your distributed team.

Use a collective memory system with LRU caching and SQLite WAL persistence to build a shared knowledge base accessible to all agents. Memory consolidation and association preserve learned patterns while automatic checkpointing enables session recovery.

Yes. Deploy specialized workers—Architects, Coders, Testers—orchestrated by a Queen agent to collaboratively design microservices architectures. Consensus ensures all agents agree on design choices while the collective memory preserves architectural patterns.

No. The Hive Mind handles queen-led coordination, memory management, and task auto-scaling automatically. Initialize with `npx claude-flow hive-mind init` and configure worker specialization; the framework manages consensus building and session control for you.

Byzantine consensus requires sufficient honest agents to achieve quorum; systems with too many faulty agents may fail to reach agreement. Scale worker count based on your fault tolerance target, and monitor consensus metrics to detect performance degradation.