<?xml version="1.0" encoding="utf-8" standalone="yes"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/">
  <channel>
    <title>Software Quality on Datalaria</title>
    <link>https://datalaria.com/en/tags/software-quality/</link>
    <description>Recent content in Software Quality on Datalaria</description>
    <generator>Hugo -- 0.148.2</generator>
    <language>en-US</language>
    <lastBuildDate>Tue, 06 Oct 2026 00:00:00 +0000</lastBuildDate>
    <atom:link href="https://datalaria.com/en/tags/software-quality/index.xml" rel="self" type="application/rss+xml" />
    <item>
      <title>Evaluating and Testing AI Agents in Production: How to Measure the Unpredictable</title>
      <link>https://datalaria.com/en/posts/evaluating_ai_agents/</link>
      <pubDate>Tue, 06 Oct 2026 00:00:00 +0000</pubDate>
      <guid>https://datalaria.com/en/posts/evaluating_ai_agents/</guid>
      <description>Why traditional unit tests and metrics like BLEU or ROUGE collapse when applied to autonomous AI agents. We engineer a 4-layer evaluation framework: tool trajectories, environment state assertions, calibrated LLM-as-a-Judge, and CI/CD red-teaming.</description>
    </item>
  </channel>
</rss>
