Agent Security
Why is policy-based access control important for AI agents?
Policy-based access control is important because AI agents can take actions across many tools and systems. Hard-coding permissions inside each agent makes access difficult to review, update, and audit. A policy-based model lets platform and security teams define what an agent can do, which tools it can call, and under what conditions. This helps keep agents aligned with least privilege as use cases grow. In Diagrid's positioning, policy is part of the production foundation for agents: durable execution handles reliable workflow progress, while identity and policy control what the agent is allowed to access.
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