Retrieval-Augmented Generation

A system where an LLM retrieves relevant passages from the web (or another source) at the moment a user asks a question, then uses those passages to generate its answer — rather than relying only on what it learned during training. Optimizing pages for clean chunking, atomic answers, and structured facts increases the chance your passages get retrieved and cited.