Plain RAG works right up until real users show up: typed keywords miss, and questions that span two files come back half answered. Agentic RAG treats retrieval as a loop the system can steer, rewriting the query, blending keyword and vector search, reranking, and retrieving again. This post upgrades the LlamaIndex pipeline with real numbers for every step, so you tune with proof instead of vibes. One quick definition first, because “agentic” leans on an idea we have not properly ... Read More