Module 6: RAG | Parent-Child Indexing - Search Small, Retrieve Big

This episode addresses the fundamental tension between retrieval precision and generation context. We explore why small chunks produce tight embeddings that retrieve well but leave the model without enough surrounding information, and why large chunks give the model context but dilute the embedding and hurt search quality. We break down parent-child indexing as the solution that decouples these two problems entirely, how child chunks handle the search and parent chunks handle the generation, and how to structure the hierarchy for documents of different complexity. We cover practical implementations in LlamaIndex and LangChain and close with guidance on when this pattern earns its place in a pipeline. By the end you will understand how to stop choosing between finding the right thing and giving the model enough to work with.