How do I evaluate an AI agent before launch?
Evaluate an AI agent against the intended workflow, not just a polished demonstration. Check task completion, forbidden actions, recovery, latency, and cost on representative cases. Define which failures block release and who can approve a change in behavior before the agent reaches a wider audience.
What does the source say?
Anthropic’s agent-evaluation guidance supports testing across actions and multi-turn runs. A task-specific acceptance rule is more informative than a generic model benchmark for deciding whether your own workflow is ready.
How can you apply this?
Write a launch worksheet with normal, ambiguous, unavailable-tool, and unauthorized-action cases. For each, state the expected outcome and inspectable evidence. Run the same set on the current and proposed configurations. Review the failed examples together and document the release decision; do not use a higher average to override a critical permission failure.
What should you watch out for?
Passing a small test set does not establish safety for every future request. Retain monitoring, escalation, and a way to reduce or stop the agent’s scope.