hive-mind-advanced

Multi-agent coordination uses a hierarchical queen-led architecture to orchestrate specialized worker agents. This approach enables task distribution, consensus-based decision-making, and shared memory across agents, allowing you to spawn a swarm for projects like full-stack development or microservices architecture where agents handle frontend, backend, database, and other specialized roles.

Byzantine consensus is a decision mechanism that reaches agreement even when some agents provide faulty or conflicting information. Use it when coordinating agents across unreliable systems or when you need robustness against individual agent failures in collective intelligence workflows.

Collective memory provides a shared, persistent knowledge base accessible to all agents in the swarm. It uses LRU caching for fast access and SQLite WAL persistence for durability, enabling agents to build on each other's work without redundant computation or lost context across sessions.

Yes, the queen-led hive mind architecture is designed for complex projects requiring specialization. You can spawn agents for frontend, backend, database, and security roles, with the queen managing task distribution, consensus decisions, and session state to automate end-to-end development workflows.

The system supports Majority, Weighted, and Byzantine consensus mechanisms. Weighted consensus lets you assign different influence levels to agents based on expertise, while Byzantine handles scenarios where some agents may be unreliable or adversarial.