How to Evaluate an AI Agent Before Launch
In this guide
An agent is not ready for production because it produced a convincing demo. It is ready when important behaviours are measurable, repeatable, observable, and bounded by clear authority.
Build a representative test set
Collect real questions, common requests, ambiguous cases, missing information, adversarial inputs, and requests that should be refused or escalated. Include examples from every workflow the agent supports.
Measure the complete task
- Answer correctness and groundedness.
- Source quality and freshness.
- Tool selection, arguments, and authorisation.
- Business-task completion.
- Escalation and refusal quality.
- Latency, cost, and recovery.
Set a launch gate
Define minimum acceptable scores, failure modes requiring human review, and the owner approving release. Monitor after launch for quality drift, stale sources, rising costs, and unsafe tool behaviour.
Related resources: RAG evaluation metrics, production observability, and prompt-injection defence.
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