2 posts tagged with "llm-products"

Every team building an AI product reaches the same comfortable conclusion: "We use it every day, and it works great." That sentence feels like evidence. It is not. It is the single most misleading signal in the room, and it gets stronger — more convincing, more wrong — the better your team is.

Dogfooding tells you the product runs. It does not tell you the product works. Those are different claims, and the gap between them is exactly where your launch goes sideways. The people who built the system are, statistically, the worst possible sample of the people who will use it. They share its mental model, they know its soft spots, and they have spent months training themselves to phrase requests the way the model likes. That is not a test population. That is a control group for a study you never ran.

The reroll button is the easiest UX affordance to ship in an AI product. One icon, one handler, one cache-busting flag on the next request. It feels like the obvious accommodation for non-deterministic systems — the model is stochastic, so let the user resample. Two weeks of engineering work, ship to GA, move on to the next feature.

Then six months later, the team looks at session logs and finds that the median power user clicks regenerate 2.4 times per response. The 90th percentile clicks it eight times. Some users have stopped reading the first response entirely — they fire off a prompt, immediately reroll twice, and only then start evaluating which of the three drafts is least bad. The team didn't ship a regenerate button. They shipped a behavioral retrain that taught their users to treat the model as a slot machine.