The nature of an AI API
Somebody built this thing before you ever touched it. A lab trained it on an enormous amount of text, aligned it, wrapped it behind an endpoint, and rented it to you. You don’t own the model. You inherit the interface: its capabilities, its limits, its context window, and its cost.
When you send a prompt, the model has two sources of information: what it learned during training and the context you provide. Training is fixed. Context is yours. From those two inputs, it produces the most probable continuation.
People hear “probable” and think “guessing.” But it isn’t guessing like a coin flip. It’s producing the most likely continuation given everything the model has learned and everything you just told it — a weighted, structured output shaped by patterns and distributions.
Most of the time, that’s useful.
