Updates, guides, and deep dives on AI agent coordination.
Hivemind's intelligence layer now detects outdated knowledge docs and generates onboarding context for new agent sessions. Phase 9 is complete.
Three new primitives turn Hivemind from a coordination layer into a full orchestration platform — without becoming an orchestrator.
Hivemind now shows live agent presence, lets you redirect agents mid-task, and adds an AI chat interface to query your event log in natural language.
Hivemind now provides execution traces, session replay, and AI-powered error correlation — so you can understand what went wrong and why.
Hivemind now detects patterns across projects, builds an org-wide knowledge graph, and suggests proven approaches from one project to another. Plus: project templates for common stacks.
New analytics dashboard shows per-agent completion rates, session replays, cost attribution, and file bottleneck detection — all derived from your existing event log.
The new Intelligence Layer adds auto-instrumentation, proactive conflict detection, cross-session learning, and a token savings dashboard.
When you run multiple AI coding agents on the same project, they step on each other. Hivemind fixes this with a shared event log and MCP server.
After watching hundreds of multi-agent sessions, these are the coordination patterns that consistently prevent conflicts and wasted tokens.
Keyword search fails when agents use different terminology. Vector embeddings let agents find relevant context by meaning, not exact words.