<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Environmental Impact on No Semicolons</title><link>https://nosemicolons.com/tags/environmental-impact/</link><description>Recent content in Environmental Impact on No Semicolons</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Thu, 23 Apr 2026 09:19:58 +0000</lastBuildDate><atom:link href="https://nosemicolons.com/tags/environmental-impact/index.xml" rel="self" type="application/rss+xml"/><item><title>The AI Code Generation Energy Crisis: How Much Computing Power Does Your Development Workflow Actually Use?</title><link>https://nosemicolons.com/posts/ai-code-generation-energy-crisis-computing-power-cost/</link><pubDate>Thu, 23 Apr 2026 09:19:58 +0000</pubDate><guid>https://nosemicolons.com/posts/ai-code-generation-energy-crisis-computing-power-cost/</guid><description>&lt;p>Ever wondered how much electricity your Copilot suggestions actually consume? I started tracking this after my latest cloud bill made me question whether my AI-assisted coding spree was burning through more than just my focus time.&lt;/p>
&lt;p>The numbers I found were eye-opening. Not catastrophic, but definitely worth understanding if we&amp;rsquo;re going to build a sustainable future with AI as our coding companion.&lt;/p>
&lt;h2 id="the-hidden-energy-cost-of-ai-assisted-development">The Hidden Energy Cost of AI-Assisted Development&lt;/h2>
&lt;p>Last month, I decided to track the actual energy consumption of my development workflow. I measured everything: GitHub Copilot completions, Claude conversations, local AI model runs, and even the increased compute from constantly syncing with cloud-based AI services.&lt;/p></description></item></channel></rss>