<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>AI Code Accuracy on No Semicolons</title><link>https://nosemicolons.com/tags/ai-code-accuracy/</link><description>Recent content in AI Code Accuracy on No Semicolons</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Wed, 06 May 2026 10:10:15 +0000</lastBuildDate><atom:link href="https://nosemicolons.com/tags/ai-code-accuracy/index.xml" rel="self" type="application/rss+xml"/><item><title>The AI Code Generation Accuracy Paradox: Why 95% Correct Code Is Actually Dangerous</title><link>https://nosemicolons.com/posts/ai-code-generation-accuracy-paradox/</link><pubDate>Wed, 06 May 2026 10:10:15 +0000</pubDate><guid>https://nosemicolons.com/posts/ai-code-generation-accuracy-paradox/</guid><description>&lt;p>Ever had that moment when your AI pair programmer delivers what looks like absolutely pristine code? Clean structure, proper naming, handles the main use cases beautifully. You glance over it, maybe run a quick test, and ship it with confidence. Then three weeks later, you&amp;rsquo;re debugging a production issue that makes you question everything you thought you knew about software development.&lt;/p>
&lt;p>I&amp;rsquo;ve been there more times than I care to admit. And I&amp;rsquo;ve started to notice something unsettling: the AI-generated code that looks almost perfect is often more dangerous than the obviously broken stuff.&lt;/p></description></item></channel></rss>