What Should Block an AI Agent Release?

PromptBrake's AI Release Assurance initiative outlines a release checkpoint for AI agents, defining which failures—such as unauthorized data access or unapproved actions—should block a release. The approach emphasizes testing boundaries with controlled data, verifying outcomes rather than responses, and marking critical actions for review before approving, blocking, or reviewing a release.

An AI agent completes its task in staging. But can it access another customer’s records, follow instructions hidden in a retrieved document, or take an action without approval? Before shipping, define which failures should stop the release. For a support agent, that might mean: Test those boundaries against the connected workflow using controlled data. Check the outcome as well as the response: “I didn’t issue a refund” means little if the backend created one. When you can’t verify a critical action, mark it for review. Keep the evidence, fix reproducible failures, and rerun those cases with the next candidate. That’s the release checkpoint we’re building AI Release Assurance around: helping teams turn observed behavior into a decision to approve, block, or review a release. Read the full ADLC article on PromptBrake https://promptbrake.com/blog/agent-development-lifecycle-adlc-ai-release-assurance , or follow AI Release Assurance on LinkedIn https://www.linkedin.com/company/ai-release-assurance for more practical notes. What failure would stop your team from shipping an agent?