<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>LLM Testing on AI VOID</title><link>https://ai-blog.noorshomelab.dev/tags/llm-testing/</link><description>Recent content in LLM Testing on AI VOID</description><generator>Hugo</generator><language>en</language><lastBuildDate>Fri, 20 Mar 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://ai-blog.noorshomelab.dev/tags/llm-testing/index.xml" rel="self" type="application/rss+xml"/><item><title>Ensuring AI Reliability: Evaluation and Guardrails</title><link>https://ai-blog.noorshomelab.dev/guides/ai-evaluation-guardrails-guide/</link><pubDate>Fri, 20 Mar 2026 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/guides/ai-evaluation-guardrails-guide/</guid><description>&lt;h2 id="welcome-to-the-guide-on-ai-evaluation-and-guardrails"&gt;Welcome to the Guide on AI Evaluation and Guardrails!&lt;/h2&gt;
&lt;p&gt;Building powerful AI systems, especially those powered by large language models (LLMs), is exciting. But deploying them reliably and safely in the real world presents unique challenges. How do we know our AI will behave as expected? How do we prevent it from generating harmful, inaccurate, or off-topic content? This guide is designed to answer these crucial questions.&lt;/p&gt;
&lt;h3 id="what-is-ai-evaluation-and-guardrails"&gt;What is AI Evaluation and Guardrails?&lt;/h3&gt;
&lt;p&gt;At its heart, &lt;strong&gt;AI Evaluation&lt;/strong&gt; is about systematically testing and validating your AI system. It&amp;rsquo;s like putting your AI through a series of rigorous checks to ensure it performs well, is fair, and is robust before it goes live. This includes everything from checking its accuracy on specific tasks to making sure it doesn&amp;rsquo;t &amp;ldquo;hallucinate&amp;rdquo; or produce nonsensical outputs.&lt;/p&gt;</description></item></channel></rss>