Building APIs that AI agents can use safely

When an AI workflow calls business APIs, ordinary integration details become important safety controls. The system may select an action from natural-language intent, but the API remains responsible for enforcing what that identity is allowed to do. Do not rely on a model prompt as the security boundary. Give actions precise shapes Prefer task-specific operations with explicit fields over a broad endpoint that accepts an arbitrary instruction. Validate input types, ranges and relationships on the server. Return structured outcomes and distinguish validation errors, permission denials, conflicts and temporary service failures. Predictable contracts make recovery easier for both people and software. Enforce delegated identity Represent the user or service on whose behalf an action is taken. Apply least privilege, short-lived credentials and explicit resource scopes. Check authorization for every operation and every object; a valid agent identity must not imply access to all customer records. Record which actor initiated a request and what the result was. Protect consequential changes Support preview or dry-run operations for high-impact actions. Use idempotency keys for requests that may be retried. Require a separate confirmation step where money, access, personal data or production state can change. Provide a reversal path when the business process allows it. Test the system, not just the prompt Exercise malformed input, replayed calls, expired credentials, concurrent updates and partial failures. Test that one user's context cannot read or change another user's data. Keep rate limits and audit signals in place. Safe agent integration comes from conventional API discipline made explicit, not from assuming the model will always choose correctly.