
This episode is about chunking, the quiet step in a RAG pipeline that decides whether your system retrieves the right answer or a confidently wrong one. It covers why the chunk is the real unit of retrieval, the tradeoff between context and precision, the main strategies teams use to split documents, and why testing your chunks against real questions matters more than picking the perfect size.
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Module 6: RAG | Data Ingestion - Before Your Documents Can Be Found

Module 6: RAG | Vector Databases - Where That Meaning Gets Stored

Module 6: RAG | Embeddings - Teaching Machines to Understand Meaning

Module 6: The RAG Pipeline - End to End
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