The AI Feature We Shipped, Measured, and Then Quietly Turned Off
Our smart search summaries looked great in demos. Real users scrolled right past them.
Our smart search summaries looked great in demos. Real users scrolled right past them.
The AI features that survive contact with real users are rarely the flashy ones. Here is why I start with the dull jobs.
Some mould is a defect, some is a feature, and the cheesemakers could tell the difference by smell.
It wrote 412 tests. I kept 260. The ones I threw away taught me more than the ones I kept.
Over 300 questions in six weeks, it was wrong 1 time in 9. It sounded sure almost every time.
Clicking around in a playground is not testing. A small, honest evaluation set will tell you more than a week of demos.
Small, unglamorous changes to context, caching and model choice cut my monthly AI costs without users noticing any difference.
Large model costs creep up quietly. A few unglamorous changes brought ours down sharply while quality held steady.
I was sure the model was wrong about ripeness. Then I checked my own labels from Monday mornings.
Eight tokens per second, no internet, no bill, and a surprising amount of usefulness for boring tasks.