What Is RAG? How Retrieval-Augmented Generation Works

A clear, current walkthrough of retrieval-augmented generation: why it exists (grounding an LLM in your own data instead of relying on what it memorized during training), how the retrieval-then-generate pipeline actually works, and where teams run into trouble in practice — the retrieval step, not the model, is almost always the real failure point. Useful if you're deciding whether RAG is the right pattern for a project, or just want a precise mental model instead of the marketing version.

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