Autonomous Project Management

Overview

Enable decentralized project coordination where multiple AI agents work independently on parallel tasks, synchronizing through a shared STATE.yaml file rather than relying on a central orchestrator. Complex projects requiring simultaneous work across multiple domains run efficiently with agents capable of autonomous execution without constant supervision.

Benefits

• Parallel execution eliminates sequential bottlenecks
• Self-organizing agents identify work from shared state
• Persistent state in version-controlled files for auditability
• Reduced coordination overhead for complex projects

Requirements

• Session management capabilities (sessions_spawn, sessions_send)
• File system read/write access for state management
• Git integration for change tracking (recommended)
• Understanding of YAML for state file structure

Technical Details

STATE.yaml file contains task registry with IDs, status (in_progress/done/blocked), ownership, dependencies, and next actions. Main session spawns specialized subagents. Each subagent reads STATE.yaml to identify assigned work, executes independently, and updates status. Other agents poll state file to discover unblocked opportunities. All changes committed to git for historical tracking.