Testing AI Agents Needs Trace Contracts

The takeaway is blunt: agent testing is closer to distributed-systems verification than snapshot-based app testing. If you only inspect final text, you miss the failures that actually matter in production.

• –Final-output snapshots still have a place, but mostly for schema checks, formatting, and narrow regression coverage
• –The stronger test is on behavior traces: did the agent check the right preconditions, call the right tool, retry safely, and avoid destructive actions
• –Rubric-based evals become useful once thresholds are tied to real business risk instead of abstract “good enough” scoring
• –Production replay, golden traces, and canary traffic are the practical backbone of agent QA because they expose drift that synthetic unit tests miss
• –Human review does not disappear; it shifts to the ambiguous edge cases where the cost of a false pass is high