AI guide
RAG Explained: Retrieval-Augmented Generation, End to End
A plain-English guide to how Retrieval-Augmented Generation actually works — why RAG exists, embeddings and semantic search, chunking, vector databases, retrieval, re-ranking, and how to evaluate a RAG system. No hype.
7 lessons·≈ 1 hr read·Free, no account
- 01What Is RAG? Why Retrieval-Augmented Generation ExistsBeginner·9 min
- 02Embeddings for RAG: Searching Text by MeaningBeginner·9 min
- 03Chunking for RAG: How to Split Documents WellIntermediate·9 min
- 04Vector Databases: Storing and Searching EmbeddingsIntermediate·9 min
- 05Retrieval in RAG: Fetching the Right ContextIntermediate·9 min
- 06Re-ranking in RAG: Putting the Best Context FirstIntermediate·8 min
- 07Evaluating RAG: How to Measure a RAG SystemIntermediate·9 min