AI Agent Control Plane
Research into a governed control plane for coordinating digital workers across an organization.
As organizations deploy hundreds or eventually thousands of AI agents, another challenge appears:
Who manages the agents?
My research explores an Agent Control Plane responsible for coordinating digital workers across an organization.
The control plane could manage:
- Agent registration
- Agent roles
- Task assignment
- Workload orchestration
- Identity
- Permissions
- Policy enforcement
- Human approvals
- Agent lifecycle
- Observability
- Audit trails
- Failure recovery
- Scaling
- Cost controls
The architecture separates AI reasoning from privileged execution.
An AI model may determine what should happen, while deterministic services, policy engines, and constrained tools determine what is actually allowed to happen.
This separation is critical for bringing autonomous agents into security-sensitive enterprise environments.
Discuss this research
This initiative is evolving. Features and architectures described here are research directions, not claims of a production release. Detailed technical documentation and demonstrations will be added as available.
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