I Built a RAG Agent on Azure AI Foundry in an Afternoon. Here's What Nobody Tells You.

Six months ago, building a RAG pipeline meant a full week of plumbing: an embedding job here, a vector store there, a retriever glued on with duct tape, and an orchestration layer that broke every time you touched it. I've built enough of these the hard way — hand-rolled vector search, custom chunking scripts, the works — to know exactly how much pain that "week" usually hides.

Last week, I rebuilt the same thing on Azure AI Foundry. It took an afternoon. Not because the underlying problem got easier — grounding an LLM in your own data is still genuinely hard — but because Microsoft finally killed most of the integration tax that used to eat the first sprint of every RAG project.