REST API Knowledge

A REST API is a convention for exposing functionality over HTTP: resources live at URLs, you act on them with verbs like GET, POST, PUT, and DELETE, and data travels as JSON. Each request is stateless — it carries everything the server needs, typically including an authentication token in a header — and the server answers with a status code (200, 401, 429, 500) that tells you what happened.

This matters because the entire AI ecosystem speaks REST. Every major model provider — OpenAI, Anthropic, Google — exposes its models as REST endpoints: you POST a JSON body containing your messages and parameters, authenticate with a bearer token or API key header, and parse a JSON response (or a streamed one) containing the generated text. Even the official SDKs are thin wrappers around these calls. When something breaks — a 429 rate limit, a 400 malformed request, a truncated stream — you debug it at the HTTP layer. Beyond consuming APIs, you will also design them: your product’s AI features become REST endpoints your frontend calls, and tools you hand to agents are frequently REST APIs under the hood.

Practically, you will exercise this constantly: crafting requests with curl or Postman, reading provider API references, handling errors with retries and exponential backoff, and building endpoints that proxy model calls securely. Master the request-response cycle here, and every provider integration in this course becomes a variation on one familiar pattern.