<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Engineering on AI VOID</title><link>https://ai-blog.noorshomelab.dev/tags/engineering/</link><description>Recent content in Engineering on AI VOID</description><generator>Hugo</generator><language>en</language><lastBuildDate>Mon, 13 Jul 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://ai-blog.noorshomelab.dev/tags/engineering/index.xml" rel="self" type="application/rss+xml"/><item><title>Meta&amp;#39;s Python Decade: Scaling Lessons for Enterprise</title><link>https://ai-blog.noorshomelab.dev/blog/meta-python-decade-scaling-lessons-enterprise/</link><pubDate>Mon, 13 Jul 2026 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/blog/meta-python-decade-scaling-lessons-enterprise/</guid><description>&lt;p&gt;For a decade, Meta has stood as a steadfast champion of Python, a commitment that might surprise those who associate the tech giant primarily with C++ or specialized languages. But what has this long-term investment truly yielded, and what can other large enterprises learn from Meta&amp;rsquo;s journey to scale Python to unprecedented levels?&lt;/p&gt;
&lt;p&gt;Meta&amp;rsquo;s decade-long commitment to Python has not only cemented its role as a critical language for the tech giant but also yielded invaluable open-source contributions and scaling insights, offering crucial lessons for other enterprises navigating large-scale Python adoption.&lt;/p&gt;</description></item></channel></rss>