Chunking Is the Hidden Lever in RAG Systems (And Everyone Gets It Wrong)
SMRTR summary
Most RAG systems fail because teams focus on embedding models and vector databases while neglecting chunking, the critical early-stage process that determines what units of meaning get indexed and retrieved. Poor chunking decisions, like blindly splitting text every 500 tokens, create garbage chunks that embed PDF noise and break semantic boundaries, causing downstream hallucinations and retrieval failures that seem to originate elsewhere.
SMRTR provides this summary for quick context. The original article belongs to DZone.
Read the original article