Temperature

Every reply is a sequence of bets.

The model ranks the next token. First place is the safe brick. Tenth place is the weird one. Temperature is the rule for how often it skips first place.

That is not a personality. It is not "smarter" or "dumber." It is a sampling setting on inference. Most chat apps hide it and pick a middle value. The moment you call an API yourself, you own the rule.

Treat it as a product decision:

• Low when the next machine has to parse the output. Code you will run. A JSON body an agent will hand to a tool. Classification, extraction, "what is the exact flag." Ask twice, you want the same receipt twice.
• Higher when you are generating options on purpose. Ten app names. Five taglines. A pile of demo scripts. You want second place to win sometimes, or every reroll is the same beige sentence.

People blame "the model" for two opposite sins. It repeats itself — the rule was too strict. It invents a package name — the rule was loose, and hallucination got a bigger door. Turning the number is not a fix for missing docs. It is a fix for how adventurous the next brick is.

Do not tune by feel on demo day. Change one setting, keep a tiny eval set — five prompts you already know — and look at whether the answers got more usable or just louder.

What this unlocks

You stop treating every bad output as a model problem. Sometimes the stack is fine and the sampling rule does not match the job: a clerk for the payload, a wanderer for the brainstorm.