Last updated on January 2, 2026 by Editorial Team
Author(s): Ravi Kumar Verma
Originally published on Towards AI.
The Complete RAG Playbook (Part 4): Evaluating and Choosing What Works
We have covered 19 RAG techniques in three parts. You’ve seen segmentation strategies, context enrichment, query transformation, rerankers, and advanced architectures. But there is one question no one wants to answer:
This article focuses on the evaluation of RAG techniques, underscoring the importance of measurement to determine which implementation works best for specific use cases. The author discusses creating appropriate evaluation datasets, applying relevant metrics, and benchmarking existing methods while analyzing their performance. Through honest evaluation, readers are equipped with the knowledge to make informed decisions about which techniques to deploy in different situations, ultimately encouraging a pragmatic approach to algorithm selection.
Read the entire blog for free on Medium.
Published via Towards AI
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Comment: The content represents the views of the contributing authors and not those of AI.
