---
title: "Discussion on \"Evaluating RAG: From Golden Datasets to LLM-as-Judge\" | Hashnode"
description: "Discussion on \"Evaluating RAG: From Golden Datasets to LLM-as-Judge\". A Retrieval-Augmented Generation system can produce a fluent answer while failing in several independent ways. It may retrieve the wrong evidence, omit a required document, misread correct context, an"
url: "https://hashnode.com/posts/evaluating-rag-from-golden-datasets-to-llm-as-judge/6a79386d5c323de5d84c5445"
---

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# [Evaluating RAG: From Golden Datasets to LLM-as-Judge](https://ahmetozel.hashnode.dev/evaluating-rag-from-golden-datasets-to-llm-as-judge?utm_source=hashnode&utm_medium=feed)

A Retrieval-Augmented Generation system can produce a fluent answer while failing in several independent ways. It may retrieve the wrong evidence, omit a required document, misread correct context, an

Aug 10 · 15 min read · ahmetozel.hashnode.dev  
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## Written by

[Ahmet Özel](https://hashnode.com/@ahmetozel)

@ahmetozel · Istanbul, Turkey

  
[View profile](https://hashnode.com/@ahmetozel)

AI Engineer. Computer Vision, RAG and LLM agents.

AI Engineer focused on computer vision (YOLO/ONNX), RAG, and LLM agents. I build and ship production AI systems and write about what I learn.

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