Part 2 — Why Does One System Need Three Chunking Strategies? And One Document Type Shouldn't Be Chunked At All

This article covers the second layer of the full-stack architecture: the Chunking Service. Chunking...

giovedì 18 giugno 2026 New tab

2,299 words~10 min read

This article covers the second layer of the full-stack architecture: the Chunking Service. Chunking strategy sets the ceiling for retrieval quality — no matter how good upstream parsing is, if chunking is wrong, nothing downstream can fix it. Core engineering insight: chunking is not a parameter tuning problem. It's a judgment problem about what constitutes the minimum semantic unit of a document.

0. The Pain Point

The first version of the system used a single chunking strategy across all documents:

Fixed 512-character chunks for everything.

Miss rate: 15%. Retrieval kept returning semantically incomplete chunks — the content was there, but only half of it.

Part 2 — Why Does One System Need Three Chunking Strategies? And One Document Type Shouldn't Be Chunked At All

Part 2 — Why Does One System Need Three Chunking Strategies? And One Document Type Shouldn't Be Chunked At All

Related reading

RAG Pipeline Chunking Strategies: Split Documents for Better Retrieval

Best Chunking Strategies for RAG Pipelines

Chunking Strategies for LLM Applications | Pinecone

What I learned building a document chunking and embedding API for RAG

Chunking Strategies for LLM Applications: A Practical Guide to Better RAG…

Part 1 — How Do Unstructured Documents Become a Searchable Knowledge Base? Five…

Related reading

RAG Pipeline Chunking Strategies: Split Documents for Better Retrieval

Best Chunking Strategies for RAG Pipelines

Chunking Strategies for LLM Applications | Pinecone

What I learned building a document chunking and embedding API for RAG

Chunking Strategies for LLM Applications: A Practical Guide to Better RAG…

Part 1 — How Do Unstructured Documents Become a Searchable Knowledge Base? Five…