<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Hosting on Afraz Ahmed</title><link>https://afraz.dev/tags/hosting/</link><description>Recent content in Hosting on Afraz Ahmed</description><generator>Hugo</generator><language>en-us</language><copyright>© Afraz Ahmed</copyright><lastBuildDate>Tue, 02 Jun 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://afraz.dev/tags/hosting/index.xml" rel="self" type="application/rss+xml"/><item><title>Applying 32 GenAI design patterns to a real project</title><link>https://afraz.dev/blog/genai-design-patterns-intro/</link><pubDate>Tue, 02 Jun 2026 00:00:00 +0000</pubDate><guid>https://afraz.dev/blog/genai-design-patterns-intro/</guid><description>&lt;p>I have been working in managed cloud hosting for about seven years. In that time, I have built a few production AI systems that handle real customer conversations and diagnose server issues. One of them handles about 30% of incoming conversations on its own. Another cut investigation time for complex server issues from 30 minutes down to about 8 minutes.&lt;/p>
&lt;p>When I picked up Lakshmanan and Hapke&amp;rsquo;s &lt;em>Generative AI Design Patterns&lt;/em> (O&amp;rsquo;Reilly, 2025), I wanted to see how many of their 32 patterns mapped to what I want to build next: a context-aware AI hosting support agent that can answer informational questions, debug complex server issues, and suggest application code optimizations for speed and security. 28 of the 32 patterns apply. The other four don&amp;rsquo;t, either because they require self-hosted models, add cost without proportional benefit, or belong to a separate system that is out of scope for what we are building here.&lt;/p></description></item></channel></rss>