Govern AI at Runtime
Stop auditing AI after the fact. This guide shows how to put policy in the execution path, so every agent action is checked before it runs and every decision leaves proof.
Your governance program approved the use case. So what stops the agent from exceeding it tomorrow? For most enterprises, the answer is a system prompt, a ticket, or a log someone will read later. Those are checkpoints. They report what went wrong after the message has left.
Govern AI at Runtime is a practitioner’s guide to inline governance, where the control evaluates each action before it executes. It ends with a checklist to test your own program.
What you’ll learn
- Where your policy really runs. Why approval alone can’t stop an agent mid-action.
- Three ways agents outrun the checkpoint. They act before the check, chain across agents, and hold broader tool access than intended.
- How mitigations become live controls. Follow one agent from discovery to a call blocked at the gateway.
- Least privilege for MCP tool calls. Govern what agents do, not just what they say.
- One record as proof. Show auditors and customers the control, the evaluation, and the block.
- A checklist to test your own execution path.
Who it’s for: AI governance leads and CISOs. It goes one level deeper than a strategy paper and needs no engineering background.
See inline governance running against your own agents. Book a demo