<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Sustainable AI Workflows on No Semicolons</title><link>https://nosemicolons.com/tags/sustainable-ai-workflows/</link><description>Recent content in Sustainable AI Workflows on No Semicolons</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Mon, 28 Sep 2026 16:17:53 +0000</lastBuildDate><atom:link href="https://nosemicolons.com/tags/sustainable-ai-workflows/index.xml" rel="self" type="application/rss+xml"/><item><title>The AI Code Generation Model Graveyard: How Dead Models Are Costing Developers $100M in Wasted Learning</title><link>https://nosemicolons.com/posts/ai-code-generation-model-graveyard-dead-models-wasted-learning/</link><pubDate>Mon, 28 Sep 2026 16:17:53 +0000</pubDate><guid>https://nosemicolons.com/posts/ai-code-generation-model-graveyard-dead-models-wasted-learning/</guid><description>&lt;p>Remember when GitHub Copilot was the only game in town? Those days feel like ancient history now. We&amp;rsquo;ve witnessed an explosion of AI coding assistants, each promising to revolutionize how we write software. But here&amp;rsquo;s the uncomfortable truth: many of these models have already joined the digital graveyard, taking millions of dollars in developer learning investment with them.&lt;/p>
&lt;p>I&amp;rsquo;ve been tracking this trend for the past two years, and the numbers are staggering. Conservative estimates suggest developers have invested over $100 million in learning tools, workflows, and integrations around AI models that no longer exist or have been fundamentally changed. Today, let&amp;rsquo;s dig into this graveyard and figure out how to build skills that actually last.&lt;/p></description></item></channel></rss>