How to Verify if an AI Agent Actually Did the Job
OgnjenAdzic · reddit · 2026-07-15
The author highlights an easily overlooked issue: a successful tool call does not mean the user's goal was actually achieved.
They give examples of failure modes when an agent handles tasks like subscriptions, scheduling, or messaging:
- Choosing the wrong action, but the API returns success
- Executing repeatedly after a timeout
- Stopping halfway through completion
- Reporting success, but the product state is actually incorrect
They argue that standard API testing only verifies the interface itself, and agent evals don't necessarily cover real-world outcomes. Therefore, they want to know how the industry tests "end-to-end completion." They are particularly interested in:
- Whether the final state is validated independently
- Or if teams mainly rely on traces, logs, and the agent's self-reported results
- How to catch those "looks successful, but actually failed" cases
Related event: AI agents in production: don’t trust narration, verify outcomes(8 posts)→
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