
Ultimate Guide to Agentic RAG
Table of Contents Introduction Traditional RAG has been a game-changer for providing LLMs with context, but we’ve all hit that wall where the system retrieves the wrong document and confidently hallucinates an answer anyway. It’s a passive, one-shot process that often feels like a librarian who hands you the first book they see and walks away without checking if it actually helps. To fix this, the industry has introduced Agentic Retrieval-Augmented Generation—affectionately known as Agentic RAG. The word “Agentic” stems from the concept of agency, meaning the system isn’t just a static pipeline but an autonomous agent capable of making










