#The problem
Running AI agents on real infrastructure requires operational controls: health monitoring, automatic escalation, and the ability to pause or kill a session before it causes damage. Without persistent context, agents repeat the same discovery work and lose institutional knowledge between sessions.
#What it does
Multi-agent platform with real-time oversight.
Core capabilities:
- Supervision layer: LLM-based failure detection that catches patterns simple heuristics miss
- Custom skills: reusable agent workflows for deployment, debugging, plan execution, code review, memory management
- MCP tools: 50+ tools spanning secrets, source control, project management, document search, infrastructure queries
- Persistent memory: cross-session context accumulation
- Observability dashboard: real-time session state, task progress, agent health
Architecture: TypeScript/Bun, k3s, PostgreSQL, Redis.
#Why it exists
One person operating 100+ production services, writing software, studying law, and building three legal AI products simultaneously. The agent platform is what makes that possible.
#Status
Active. Powers all other projects on this site.