An Autonomous AI Control Plane for Governing Agent Behavior at Runtime
1 points
16 hours ago
| 2 comments
| HN
I built a working autonomous control plane designed to govern how AI-driven workflows and agents behave at runtime. Instead of relying on post-incident logs or manual reviews, the system enforces policies before actions occur, simulates changes safely, and proposes corrective actions when violations happen.

The platform converts high-level human intent into structured, executable workflows using event-driven orchestration. It combines policy-first enforcement, asynchronous agent coordination, and a simulation layer so changes can be evaluated before being deployed into a real environment. The goal is to make autonomy safer and more controllable, not just more capable.

This is a real, end-to-end system (not a concept or chatbot), built as a horizontal control plane rather than a domain-specific application. I’m sharing it here to get technical feedback from others thinking about agentic systems, governance, and runtime control.

Kase1111
15 hours ago
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Solid work—shipping a full proactive control plane with simulation and pre-action enforcement is exactly the kind of governance layer agentic systems need right now. I’ve been exploring a related angle on runtime governance: making the policies, decision trails, and enforcement actions themselves live in immutable natural language discourse. Curious how you’re handling policy expression and audit trails today. Either way, inspiring stuff—keep shipping!
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Yokohiii
16 hours ago
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You forgot the link.
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