Don't RAG Until You Have To

The problem RAG is trying to solve: you have rich data, you have a question, and you want to apply intelligence to getting the answer. Why build a RAG pipeline when AI can already do a lot of that for you?

First pass: give AI access to the data and let it figure it out. MCP tools, Notion integrations, context7 for API docs. Just point it at the source and ask.

If that doesn’t work, it might be a skill issue. As in, literally add a skill. Some search tips, workflow-specific guidance, a nudge on where to look. That alone gets you surprisingly far.

If that doesn’t work, then yeah, there are cases where the complexity investment in RAG is worth it. That’s when you make the jump. Not before.

As somebody who’s built RAG systems: don’t sign up willingly just because it sounds cool.

If you’re curious about semantic search and just want to try it locally, qmd pretty much does it out of the box.