One post tagged with "ml"

Here's a scenario that plays out at most AI product teams: someone on leadership asks whether the new copywriting model is better than the old one. The team runs their eval suite, accuracy numbers look good, and they ship. Three weeks later, the marketing team quietly goes back to using the old model because the new one "sounds off." The accuracy metrics were real. They just measured the wrong thing.

This is the AI taste problem. It shows up wherever your outputs are subjective — copywriting, design suggestions, creative content, tone adjustments, style recommendations. When there's no objective ground truth, traditional ML evaluation frameworks give you a false sense of confidence. And most teams don't have a systematic answer for what to do instead.