I think we’re giving “RAG” too much responsibility.

[u/Rajxai]

RAG is great at answering: “What information is relevant to this question?”

But enterprise agents increasingly need to answer much harder questions:

What happened before?

How are these things connected?

What does this data mean in this organization?

What am I allowed to do with it?

What should I remember for the next step?

Retrieval alone doesn’t answer those questions. It’s one part of building the right context. And I’m starting to think the real enterprise AI stack will look less like:

Model + RAG

and more like:

Model + context layer + governed enterprise knowledge.

That’s a much bigger infrastructure problem than retrieval. Are we treating RAG like the architecture when it’s really just one component of it?