Trace agent decision-making, tool selection, and reasoning chains
Instrument safety checks, content filters, and guardrails for agent outputs
Strategies for evaluating agents in production - sampling, baselines, and regression detection
Track prompt versions, A/B test variants, and measure prompt performance
Instrument error handling, retries, fallbacks, and failure patterns
Instrument evaluation metrics, quality scores, and feedback loops
Instrument human approval workflows, feedback loops, and escalations
Plan what to measure in AI agent systems using tiered approach