What is RAG? A simple explanation for developers

RAG (Retrieval-Augmented Generation) means: load your documents, split them into chunks, turn chunks into embeddings, store in a vector store. When the user asks a question, you retrieve relevant chunks and pass them plus the question to an LLM. The model answers using your data. We cover document loaders, text splitters, vector stores, and the full pipeline in our AI track.