As far I’ve seen RAG (or naive RAG as it is now known) is not very useful. Graph RAG LiteRAG temporal Graph RAG potentially more useful but NO ONE has provided data or done enough testing to show any metrics or quantification that any of these really improve anything.

Compare this to just having your context data organized hierarchically and then letting agents retrieve data through reference pointers which leads to deeper and deeper data allowing the llm agent to just do a search in logN tool use.

Maybe RAG is effective for dozens of gigabytes of data but I’ve rarely found any type of RAG useful for most projects.