Hive Mind Advanced

This is a sophisticated multi-agent orchestration system that implements queen-led architecture where a coordinator agent directs specialized workers (researchers, coders, testers, architects) through Byzantine consensus and shared SQLite memory. You'd use this when a task needs genuine division of labor, like building a full microservices architecture where different agents handle API design, implementation, testing, and documentation in parallel. The collective memory system with LRU caching and association tracking is genuinely clever, letting agents build on each other's work instead of starting fresh. Fair warning though: the complexity overhead only pays off for substantial projects. For simple tasks, you're just adding coordination cost. The 84.8% SWE-Bench solve rate and 10-20x batch spawning improvement suggest it actually works when the problem fits the paradigm.