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The blog post explains RAG chunking, highlighting techniques like fixed-size (with sliding window), document-based (using structure), LLM-based (for semantic understanding), and late chunking (on-demand). It stresses best practices like experimentation, context preservation, and metadata for optimal LLM performance.