Medium LLM
RAG from Scratch [Part 3]: Chunking — The Decision That Makes or Breaks Your Retrieval
context
What happened
Part 3 of a 'RAG from Scratch' series focusing on document chunking. It explains the trade-offs of chunk sizes (precision vs. context) and why chunking strategy is a critical, often overlooked lever in retrieval performance.
Why it matters
Optimizing chunk size and boundaries is the most cost-effective way to improve RAG retrieval precision without changing models.
The take
Chunking is indeed one of the most practical levers for improving RAG. While this article covers foundational concepts (like chunk size trade-offs), it is a solid reminder that retrieval quality starts with data preparation, not just vector search.
Do this
Review your current RAG pipeline's chunking strategy; experiment with semantic chunking instead of fixed-character limits.
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