AI · Term
Retrieval-Augmented Generation (RAG)
Retrieval-Augmented Generation (RAG) is a technique where an AI model retrieves relevant documents at query time and uses them to ground its generated answer.
RAG is why current, well-structured web content matters for AI visibility: when an engine retrieves passages to answer a question, the sources it pulls are the ones it can cite. Content written answer-first and marked up clearly is easier to retrieve accurately.
RAG is one part of how modern AI systems work. For the bigger picture — how large language models are built and how retrieval fits in — read What Are Large Language Models (LLMs)?
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