What is Agentic RAG, in simple terms, and how does it d...

Basic RAG is one fixed sequence no matter what’s asked: embed the query, search the vector store, take the top handful of chunks, generate an answer from them. The steps never change based on how the first search went.

Agentic RAG adds a reasoning layer on top of that same machinery. The agent decides whether the question is even about billing, technical docs, or something else, and routes accordingly; it evaluates whether what came back is actually good enough; and if it isn’t, it rewrites the query and tries again rather than answering with a weak result. A billing question that first pulls stale pricing chunks gets a second, better-targeted search instead of an answer built on outdated numbers.

The one-line version worth remembering: basic RAG is a fixed pipeline, Agentic RAG is adaptive retrieval — the agent adjusts its search strategy based on what it actually finds, rather than running the same steps regardless of outcome.