RAG (Retrieval-Augmented Generation)
A pattern where relevant documents are fetched from a knowledge base and injected into the prompt before the model answers.
RAG lets a model answer about content it never saw during training. Done well, it cites sources and reduces hallucinations. Done poorly, it dumps too much noise into the context window.