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What is AI agent governance?
Understand who should own an AI agent, what it may do, and how to review its actions.
An AI agent governance framework for engineering teams
Build a repeatable review process for agent ownership, access, testing and changes.
Write an AI governance policy for agents
Use a practical policy structure that connects agent permissions to owners and enforcement.
AI agent access control at the action boundary
Decide which agent may perform which action on which resource, and enforce the decision.
Human in the loop AI that people can actually review
Design approval steps that give a person enough context and authority to make a useful decision.
How to assess the risk of an AI agent
Review the harm an agent could cause, the controls that limit it, and the evidence still missing.
What belongs in an AI agent audit trail
Record agent requests, access decisions and outcomes without copying secrets into your logs.
Least privilege for AI agents
Limit an agent's authority to the actions, resources and time its task actually needs.
AI agent identity and delegated access
Keep the agent, the person requesting work and the executing service identifiable throughout a task.
AI governance vs AI security
Understand how governance decisions and security controls work together in an agent deployment.
Production access for AI agents
Give an agent useful operational access with explicit scope, approval rules and recoverable execution.
Incident response for an AI agent
Contain unexpected agent activity, preserve evidence and restore access only after checking the cause.
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