RAG Videos

Retrieval-augmented generation is how most real products ground language models in their own data, and the details — chunking, embeddings, hybrid search, re-ranking — make or break answer quality. Video walkthroughs are particularly useful here because RAG is a pipeline problem: seeing someone assemble and debug one end to end teaches lessons that documentation rarely captures. The videos below range from beginner pipelines to production retrieval systems at scale. This page aggregates RAG videos from every creator we track, so you can compare how official labs, educators, and practitioners approach the same subject. Videos are a starting point, not the whole picture. Below the video feed you will find hand-picked learning guides that explain the underlying concepts in depth, popular open-source GitHub repositories where the ideas live as code, and the AI tools most closely associated with RAG. We also surface the latest news coverage and research related to the topic, because a release video, its paper, and its press coverage each tell a different part of the story. Together they make this page a practical hub for going from "I watched a video about RAG" to actually understanding and building with it.