100%. This is why RAG and "classical search" will converge for non-trivial use cases. The folks who are doing RAG well still rely on many tried-and-true tricks

100%. This is why RAG and "classical search" will converge for non-trivial use cases. The folks who are doing RAG well still rely on many tried-and-true tricks of the trade: combining semantic search with keyword-based search, using graphs, doing re-ranking, etc. etc. Yet most discussions of RAG on the internet seem to promise consistently awesome query output by just jamming together some embeddings and an LLM, which doesn't pan out in practice.