09/01/2026
Most teams design for when AI works. Nobody designs for when it doesn't. That's where trust collapses.
Traditional errors are obvious. AI errors are confident. The model doesn't know it's wrong, returns the output anyway, and the user has no idea the answer is made up.
AI fails in six distinct ways: fabrication, partial corruption, semantic drift, scope failure, intent misalignment, and system failure. And each needs a different response.
Users can forgive AI getting it wrong. What they can't forgive is the product pretending it didn't. Show uncertainty. Preserve the user's input. Name what went wrong. Give a specific way forward.
The AI features that build the most trust aren't the most accurate. They're the ones that behave well when the model is wrong.
Learn more in our latest blog at the link in bio.