2 posts tagged with "change-management"

Your AI feature works. It passes every benchmark you built. It handles edge cases your team spent weeks stress-testing. Users in the pilot loved it. Your model isn't hallucinating. Latency is under 300ms. The eval suite is green.

Then six months go by and it still isn't in production. Legal wants three more reviews. A senior VP is concerned about "scope." The team that owns the adjacent workflow says they weren't consulted. Finance says the ROI model needs rework. You're told to "socialize it more broadly."

This is the organizational immune system at work — and it kills more AI projects than bad models ever will.

A team added three words to a customer service prompt to make it "more conversational." Within hours, structured-output error rates spiked and a revenue-generating pipeline stalled. Engineers spent most of a day debugging infrastructure and code before anyone thought to look at the prompt. There was no version history. There was no rollback. The three-word change had been made inline, in a config file, by a product manager who had no reason to think it was risky.

This is the canonical production prompt incident. Variations of it play out at companies of every size, and the root cause is almost always the same: prompts were treated as ephemeral configuration instead of software.