Originally published on AI Tech Connect.
What chunking strategy you use is the single highest-leverage decision in RAG retrieval quality — it sets the ceiling on everything downstream. Three production strategies compared with benchmark data: fixed chunking (the reliable baseline), semantic chunking (best for narrative text), and hierarchical chunking (three to five times F1 improvement on structured documents). The "measure before you switch" rule: always run your golden eval set against each chunking strategy before deploying a change to production. Why chunking is the highest-leverage RAG decision Most RAG failures happen at retrieval, not at generation. The language model at the end of the pipeline can only reason from what retrieval hands it — if the right passage never reaches the context window, no amount of prompting,…
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