What is an LLM API?

An LLM API is a way for software to use a language model programmatically — sending it text and getting a response back in code, rather than typing into a chat window. It's how developers build AI into their own apps. Instead of a person chatting with the model, a program makes a request to the provider's servers: here's the prompt (and some settings), send back the model's answer.

The application can then do whatever it wants with that response — display it, store it, or feed it into the next step.

What is an LLM API used for?

It's the backbone of almost every AI product you use that isn't the chatbot itself. A support tool that drafts replies, an app that summarizes documents, a coding assistant in your editor — under the hood they're all making LLM API calls. The API turns a model from something you talk to into a building block you can wire into any software, which is what lets a small team add real AI features without training a model of their own.

What do you need to know to work with one?

Calling an API introduces a handful of practical concepts that never come up in a chat window:

• API keys — a secret credential that authenticates your requests and ties usage to your account.
• Tokens and billing — you're charged per token (roughly, per chunk of text) for both what you send and what you get back.
• Parameters — settings like temperature let you dial responses from focused and predictable to loose and creative.
• Rate limits and errors — providers cap how fast you can call, and requests occasionally fail, so real apps retry and handle failures gracefully.

How is it different from using a chatbot?

A chatbot is built for a person: you type, you read, you're done. An API is built for other software — no interface, no human in the loop by default, just structured requests and responses that your code controls. That difference is what lets you run the model at scale: thousands of calls, wired into steps a person never sees.