<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Software Quality on AI VOID</title><link>https://ai-blog.noorshomelab.dev/tags/software-quality/</link><description>Recent content in Software Quality on AI VOID</description><generator>Hugo</generator><language>en</language><lastBuildDate>Thu, 18 Jun 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://ai-blog.noorshomelab.dev/tags/software-quality/index.xml" rel="self" type="application/rss+xml"/><item><title>Testing Principles for AI Agents: Adapting Software Engineering Practices</title><link>https://ai-blog.noorshomelab.dev/harness-engineering-ai-agents-2026/testing-ai-agents/</link><pubDate>Thu, 18 Jun 2026 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/harness-engineering-ai-agents-2026/testing-ai-agents/</guid><description>&lt;h2 id="introduction-to-agent-testing"&gt;Introduction to Agent Testing&lt;/h2&gt;
&lt;p&gt;Welcome back, future Harness Engineers! In the previous chapters, we laid the groundwork for building robust AI agents by focusing on systematic environments, state management, control systems, and observability. Now, it&amp;rsquo;s time to tackle one of the most critical aspects of any reliable software system: &lt;strong&gt;testing&lt;/strong&gt;.&lt;/p&gt;
&lt;p&gt;Just as traditional software requires rigorous testing to ensure correctness and stability, AI agents demand their own specialized testing strategies. However, testing agentic systems presents unique challenges due to their non-deterministic nature, reliance on external models, and complex interactions with tools and environments.&lt;/p&gt;</description></item></channel></rss>