The date format that broke my production AI agent (and the boring fix)

Short summary

An AI agent silently corrupted production data by misinterpreting an ambiguous date format—the model performed flawlessly on 43 test cases but failed on real-world variants sent from an upstream system. The solution was straightforward: add input validation before the agent processes data and output validation before writing results to the database. The broader lesson: demo capability doesn't equal production reliability; wrap all production agents with validators that route failures to review queues rather than risking silent data corruption.

• •Agent wrote dates as 1970 due to unrecognized date format—no error, just wrong output
• •Added validators: one before agent input, one before database writes
• •Production fails differently than demos; reliability requires wrapping agent logic with strict schema checks

Generated with AI, which can make mistakes.