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How to Validate AI Output Before You Trust It
AI agents will tell you everything works. Here is how to validate AI output when the mistakes are ones no human would ever make.
Peter and Dave compare notes from building software, training material, and presentations with AI. The problems they keep running into are strange ones: the wrong database ID dropped into a system, 236 passing tests that test nothing, and five layers of abstraction added to a solution that needed none of them. Their answer borrows from good agile practice. Define what validation means before the agent starts, the same way a team agrees on its definition of done…
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