Understanding Retrieval in RAG Systems: Why Chunk Size Matters
Last Updated on December 29, 2025 by Editorial Team
Author(s): Sarah Lea
Originally published on Towards AI.
A step-by-step retrieval guide using sentence transformers, chunk size and similarity scores.
These are exactly the kinds of answers we expect today from retrieval-augmented generation systems. You upload a PDF, ask a few questions, and get back plausible and often usable answers. RAG systems are often surprisingly reliable.
This article explores the mechanics of retrieval-augmented generation (RAG) systems by building a simple RAG system that handles three predefined questions using specific chunk sizes and evaluates the influence of chunk size on answer reliability. It demonstrates that while smaller chunks can lead to fragmented and incomplete answers, larger chunks provide more coherent responses. The author addresses potential uncertainties in the retrieval process and highlights the importance of tailoring chunk sizes to enhance retrieval accuracy and maintain the integrity of the generated answers.
Read the full blog for free on Medium.
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