The Problem RAG Solves Do you want to learn how to build a RAG Pipeline from Scratch? Every large language model has a knowledge cutoff. It knows what it was trained on, and nothing beyond that. Ask a frontier model about a document it has never seen, a database record updated this morning, or a policy that changed last week, and it will either hallucinate an answer or tell you it does not know. For the vast majority of real enterprise AI applications, this is a fundamental limitation. Retrieval-Augmented Generation (RAG) solves it. Rather than relying solely on what is baked into the model’s weights, RAG retrieves relevant content from…