In your test environment your AI looks brilliant. Every record is clean. Every field is filled. It is a world that does not actually exist.

Then the system hits production. Half empty forms. Free text chaos. Contradictory entries from three different systems of record.

You were never testing AI performance. You were testing how well it handles your imagination of reality.

This episode walks through why AI systems that perform well in testing fail in production. Why the gap between curated test data and messy real data is where your failure rate actually lives. Why AI models silently improvise when data is incomplete and nobody logs it. And what production-realistic evaluation actually requires.

This is Maya. New episodes three times a week.

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