Question 1

What is Agent Runtime Governance?

Accepted Answer

Agent Runtime Governance (ARG) is the discipline of controlling what autonomous AI agents do while they run. It decides each governed action against policy before it executes, keeps authority scoped to the task, contains an agent that goes off course, and records what was decided. Watchlight AI defined the category in February 2026.

Question 2

What is Agentic IAM?

Accepted Answer

Agentic IAM is the identity architecture for AI agents. It extends your IAM, PAM, and IGA to cover how people delegate to agents, how agents delegate to each other, how agents reach tools and MCP servers, and how that authority is narrowed, expired, and revoked.

Question 3

How is Agent Runtime Governance different from IAM?

Accepted Answer

IAM establishes who an agent is and what it can reach. Agent Runtime Governance decides whether a specific action should happen now, for this task, under this authority. The two work together: identity stays the foundation, and governance acts on what the agent does with the access it holds.

Question 4

How do you authorize AI agents?

Accepted Answer

Authorize each action at the moment it runs. Scope authority to the task, evaluate the action against deterministic policy outside the agent, and refuse what falls outside the scope. A valid token shows the agent can reach a system. It does not show this action should happen.

Question 5

How do you secure agent-to-agent delegation?

Accepted Answer

Make every handoff produce authority equal to or narrower than what the parent holds, in actions, resources, and time, and refuse any request for more. Build the chain from records the agent cannot edit, so a sub-agent cannot claim authority it was never given.

Question 6

How do you stop an AI agent mid-run?

Accepted Answer

You need responses beyond allow and deny, written into policy ahead of time. Stop the run, quarantine the agent until an operator releases it, cut off the sub-agents it started, or revoke its trust. Each reaches a different scope, so you can act without taking down a whole workflow.

Question 7

How do you audit what AI agents did?

Accepted Answer

Record each decision when it is made, along with the run and sub-agent it belongs to, the policy that decided it, and the reason. Logs stitched together after an incident show timing. A record written at decision time shows why an action was allowed or refused.

Question 8

How do you govern MCP servers and tool calls?

Accepted Answer

Know which MCP servers and agents exist, assign each an owner and an identity, then evaluate tool calls against policy before they execute. Enforcing in two places helps: an in-process plugin sees the agent's plan and intent, and a proxy governs traffic on the wire.

Question 9

Are AI guardrails the same as Agent Runtime Governance?

Accepted Answer

No. Guardrails mostly inspect what goes into and comes out of a model. Agent Runtime Governance acts on what the agent then tries to do: its tool calls, its delegations, and its authority across a run. Many teams use both.

Question 10

What is an AI agent control plane?

Accepted Answer

An agent control plane is the layer that sits outside your agents and governs them across frameworks: identity, policy, enforcement, containment, and evidence. Watchlight AI Beacon is the control plane for Agent Runtime Governance.

Question 11

Should an LLM make authorization decisions for agents?

Accepted Answer

No. An authorization decision should be deterministic, so the same request under the same policy gets the same answer and a model cannot be talked out of it. Watchlight AI Beacon keeps language models out of the authorization decision.

Question 12

Which compliance frameworks apply to AI agents?

Accepted Answer

ISO/IEC 42001, NIST AI RMF, and the EU AI Act are the usual starting points, and all three expect controls you can demonstrate. The Agent Compliance Map shows how Beacon enforces and evidences agent controls across nine frameworks and 73 requirements.

Question 13

Does a governance product make you compliant?

Accepted Answer

No. Compliance belongs to your whole program, and your auditor decides. A product can enforce the agent controls that program requires and produce evidence for them. The Agent Compliance Map marks which requirements Beacon supports and how.

Question 14

How do you start governing AI agents?

Accepted Answer

Pick one real agent workflow, assess its fit and readiness, then pilot governance on it before you deploy widely. Developers can start with Watchlight Developer Edition, which is free and open source and runs on their own machine.

AI agent governance, answered