RAG isn't an AI problem. It's a data engineering problem wearing an AI hat.

The tutorial-to-production gap

Every RAG tutorial follows the same arc. Load some documents. Chunk them. Embed them into a vector database. Wire up a retrieval step before the LLM call. Ask a question, get a grounded answer. Twenty minutes, looks great, feels like the future.

Then you try to run it on real data, with real users, at real scale, and you discover that the AI part of RAG was the easy part. The hard part is everything the tutorial skipped.

The problems that surface after the demo

Document lifecycle management