You will be able to
- Explain why documents are chunked, and which model limits bound chunk size.
- Chunk by fixed size in characters, words or tokens, and show how boundaries break facts.
- Size overlap to the length of the text that must stay whole, and count what it costs.
- Split documents recursively along their own structure (sections, paragraphs, sentences).
- Weigh smaller against larger chunks and choose a size by experiment.
- Add context to chunks (metadata, entities, questions, generated context) so they can be found.
- Rewrite conversational queries so they stand on their own, and decline to guess when they can't be resolved.
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AI Engineering · Chip Huyen, 2025
Chip Huyen. O'Reilly. Used: Ch. 6 "RAG and Agents": "Retrieval Optimization" > "Chunking strategy", "Query rewriting", "Contextual retrieval".
Hands-On Large Language Models · Jay Alammar & Maarten Grootendorst, 2024
Jay Alammar & Maarten Grootendorst. O'Reilly. Used: Ch. 8 "Semantic Search and Retrieval-Augmented Generation": "Chunking long texts"; "Advanced RAG Techniques" > "Query rewriting".
Introducing Contextual Retrieval · Anthropic, 2024
Anthropic. Used: Performance improvements (fetched 2026-10-23). Open source