What is RAG in AI?

RAG (Retrieval Augmented Generation) is an AI technique where relevant information — such as documentation, files, or web data — is retrieved first and then provided as context to a language model before it generates an answer. This allows the model to go beyond its training data by grounding responses in up-to-date or domain-specific information. The core idea: find first, then generate.