Whole documents often contain several topics, so one embedding blurs their meaning. Retrieving the entire document also wastes context tokens and can hide the exact passage needed for an answer.
Chunking creates smaller units that are easier to match and fit into a prompt. Each chunk should carry metadata that connects it to the source, section, page, and access policy.
Chunks that are too small lose context; chunks that are too large reduce retrieval precision. Start with natural sections or paragraphs, then tune size and overlap on real questions. Preserve a way to expand around a winning chunk when neighboring text changes its meaning.
Rewriting in plainer words…
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