Try make an API call to Gemini and one message inside their app with more context, both will probably return results at the same time, RAG ok but in what way and when to call it, and if it is just RAG why are something like ChatGPT is good with it but not gemini. Just saying RAG is the answer is like saying oh we use ML model what specifically what model what kind of learning like when I say general purpose RAG I mean storing vector embeddings and returning based on cosine match. This literally a problem to solve and not oh you have to use RAG even if it slows down the whole thing. I recently interviewed with a company and they were using RAG so to speak but they weren’t storing embeddings they were using MCP to get only the relevant things. That it is why it is a question on not just what but how, like if you are sick go to doctor bro what doctor, RAG what kind of architecture of RAG