What controls belong in an AI agent governance program?

An AI agent governance program should include workload identity, tool-access policy, approval workflows, audit logs, data-boundary rules, observability, incident response, and lifecycle controls for agents moving from prototype to production. It should also define who owns reliability, who approves sensitive tool access, and how changes are reviewed. Governance is broader than security; it includes accountability, traceability, and operational control. Diagrid's North Star aligns with this direction by positioning Catalyst around AI agent reliability, security, and governance, especially for enterprises where platform and CISO teams must approve production agent deployments.