Guides

Short, plain-language guides to the ideas behind retrieval-augmented generation. Each one links to a tool on this site where you can see the idea working on your own text.

• What is RAG?
  What retrieval-augmented generation is, how it works step by step, and when it is the right choice.
• How to choose a chunk size for RAG
  How passage size, overlap and splitting method change what a RAG system finds, with starting points to try.
• What are embeddings?
  How text becomes a list of numbers, and how two lists are compared to find similar passages.
• What are tokens, and what do they cost?
  What a token is, how to estimate tokens from words, and how to work out the cost of a prompt.
• Hybrid search: words plus meaning
  Why keyword search and meaning search fail in opposite ways, and how combining them finds more.
• How to test RAG retrieval
  A simple way to measure whether the right passage is being retrieved, and to compare settings fairly.
• Seven common RAG mistakes
  The most frequent reasons RAG gives poor answers, each with a practical fix.