How One Developer Built a Six-Role AI Agent System to Run His Homelab Projects

A developer has shared how he structured a single self-hosted AI model into six distinct agent profiles — chief of staff, scout, builder, security, writer, and IT admin — each assigned a narrow, specific role. The agents do not communicate directly with one another; instead, they share a Kanban-style task board where work moves through columns from idea to completion. A core design principle governs the entire setup: scripts and deterministic tools gather real-world facts, while AI models are only permitted to interpret, write, or route — never to independently source data. This separation is meant to prevent hallucination-driven errors, since the developer found that allowing models to freely research facts led to unreliable outputs. The result is a transparent, inspectable workflow where any agent can be restarted or replaced without losing progress, as all state is stored on the shared board rather than in conversation history.