<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Software Evolution on No Semicolons</title><link>https://nosemicolons.com/tags/software-evolution/</link><description>Recent content in Software Evolution on No Semicolons</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Fri, 17 Apr 2026 09:09:47 +0000</lastBuildDate><atom:link href="https://nosemicolons.com/tags/software-evolution/index.xml" rel="self" type="application/rss+xml"/><item><title>The AI Code Evolution Timeline: How Generated Code Changes After 6 Months in Production</title><link>https://nosemicolons.com/posts/ai-code-evolution-timeline-production-changes/</link><pubDate>Fri, 17 Apr 2026 09:09:47 +0000</pubDate><guid>https://nosemicolons.com/posts/ai-code-evolution-timeline-production-changes/</guid><description>&lt;p>Ever wonder what happens to that AI-generated code after it ships? You know the feeling — Claude or Copilot spits out a beautiful function, you tweak it a bit, tests pass, and off it goes to production. But six months later, you&amp;rsquo;re staring at that same code wondering why it&amp;rsquo;s causing issues or how it&amp;rsquo;s somehow become the most reliable part of your system.&lt;/p>
&lt;p>I&amp;rsquo;ve been obsessively tracking AI-generated code across several production systems for the past year, and the patterns that emerged surprised me. Let me share what I learned about how our AI-assisted code actually behaves in the wild.&lt;/p></description></item></channel></rss>