Key Security and Safety Checks Teams Should Run Before Releasing an AI Agent
Before deploying an AI agent to production, development teams must define which failure types should block a release entirely. Critical red lines include the agent accessing records belonging to other customers, following unauthorized instructions embedded in retrieved documents, or performing actions like issuing refunds without required approvals. Testing should cover the full connected workflow using controlled data, verifying both the agent's response and actual backend outcomes to catch silent failures. Any critical action that cannot be verified should be flagged for manual review, with evidence retained and failed cases retested in subsequent builds. This structured approach forms the basis of a release checkpoint framework aimed at helping teams make confident approve, block, or review decisions for AI agent deployments.
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