by Amit Shekhar · 10 September 2026
Chunking Strategies for RAG
Chunking Strategies for RAG, the art of cutting a big document into smaller pieces so that an AI system can find the right piece at the right time. We will also see what RAG is, why chunking is needed at all, what happens when we chunk badly, the most useful chunking strategies one by one, how to pick the chunk size and the overlap, and where each strategy works well and where it fails.
Read on Outcome School ↗then come back to lock it in
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What this article covers
- What is RAG?
- What is a chunk?
- Why do we need chunking?
- How retrieval actually works
- What happens when we chunk badly
- Fixed-size chunking
- Chunking by sentence
- Recursive chunking
- Document structure based chunking
- Semantic chunking
- Contextual chunking
- Small-to-big chunking
- Agentic chunking
- Chunk overlap
- How to choose the chunk size
- Comparison of all the strategies
- Common mistakes
The article lives on outcomeschool.com. Read it there, then come back: the tutor in the margin has read it and will answer questions, and the questions below check what stayed.