Evaluation & Operations
How to Evaluate AI Agents
Measure task success, tool behavior, evidence quality, safety, cost, and consistency across full trajectories.
Evaluate outcomes and paths
Final-answer quality is not enough. Record whether the agent chose appropriate tools, respected constraints, recovered from errors, and stopped for the right reason.
Use layered evaluators
Combine deterministic checks, human review, domain-specific scoring, and carefully calibrated model graders. Each catches different failures and none should be treated as universally authoritative.
Test changes continuously
Run a stable evaluation set when prompts, tools, models, or policies change. Compare quality alongside latency and cost so an apparent improvement does not hide a practical regression.