RAG Document Chunking Strategies

Poor chunking destroys RAG performance before the LLM even sees the prompt. You must balance semantic coherence with embedding model token limits.

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Fixed-Size vs Semantic Chunking

Naive fixed-size chunking (e.g., 500 characters) frequently splits sentences or paragraphs in half, destroying meaning. Semantic chunking (using tools like LangChain's RecursiveCharacterTextSplitter) respects sentence boundaries and paragraph breaks.

Overlap is Critical

Always implement chunk overlap (e.g., 20%). This ensures that concepts spanning a chunk boundary are captured in at least one embedding, preventing retrieval misses.

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