LLM integrations look simple in demos. In production, they fail in ways most tutorials never cover.

What you will learn in this guide:

How to structure an LLM integration that does not block your API

How to implement streaming responses for better user experience

How to manage token costs before they become a budget problem

How to version prompts without redeploying your application

How to build graceful fallback when the AI call fails or times out

The Problem With Most AI Integration Tutorials

Most LLM integration guides stop at "call the API, log the response." That is enough to demo.…