<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>LLM Evaluation on DataAgentX</title><link>https://e343c64b.dataagentx.pages.dev/en/tags/llm-evaluation/</link><description>Recent content in LLM Evaluation on DataAgentX</description><generator>Hugo</generator><language>en-US</language><lastBuildDate>Thu, 10 Sep 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://e343c64b.dataagentx.pages.dev/en/tags/llm-evaluation/index.xml" rel="self" type="application/rss+xml"/><item><title>If the SQL Runs, Can You Trust the Data Agent Answer?</title><link>https://e343c64b.dataagentx.pages.dev/en/tech/20260910-evaluation/</link><pubDate>Thu, 10 Sep 2026 00:00:00 +0000</pubDate><guid>https://e343c64b.dataagentx.pages.dev/en/tech/20260910-evaluation/</guid><description>&lt;p&gt;A successful query, attractive chart, and complete report do not independently make an answer trustworthy. The agent may have selected the wrong source, bound the wrong metric, executed correct SQL over incomplete data, and then described correlation as causation.&lt;/p&gt;&#10;&lt;p&gt;One accuracy score compresses these failures into a number and hides high-cost errors. A better evaluation follows the analysis chain layer by layer and sends each failure back to the component that can repair it.&lt;/p&gt;</description></item></channel></rss>