<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>OpenAI Agents SDK on AI VOID</title><link>https://ai-blog.noorshomelab.dev/tags/openai-agents-sdk/</link><description>Recent content in OpenAI Agents SDK on AI VOID</description><generator>Hugo</generator><language>en</language><lastBuildDate>Sun, 08 Feb 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://ai-blog.noorshomelab.dev/tags/openai-agents-sdk/index.xml" rel="self" type="application/rss+xml"/><item><title>Chapter 5: Multi-Agent Orchestration: Collaborative Customer Service Workflows</title><link>https://ai-blog.noorshomelab.dev/openai-cs-agents-guide-2026/05-multi-agent-orchestration/</link><pubDate>Sun, 08 Feb 2026 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/openai-cs-agents-guide-2026/05-multi-agent-orchestration/</guid><description>&lt;h2 id="chapter-5-multi-agent-orchestration-collaborative-customer-service-workflows"&gt;Chapter 5: Multi-Agent Orchestration: Collaborative Customer Service Workflows&lt;/h2&gt;
&lt;p&gt;Welcome back, aspiring AI architect! In previous chapters, we laid the groundwork by understanding the fundamentals of single AI agents, their components, and how they interact with tools. But what happens when a customer&amp;rsquo;s query is complex, requiring expertise from different departments, or when a single agent might become overwhelmed? This is where the true power of AI agents shines: through &lt;strong&gt;multi-agent orchestration&lt;/strong&gt;.&lt;/p&gt;</description></item><item><title>Chapter 8: Building a Real-World Customer Support Agent (Project 1)</title><link>https://ai-blog.noorshomelab.dev/openai-cs-agents-guide-2026/08-project-customer-support/</link><pubDate>Sun, 08 Feb 2026 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/openai-cs-agents-guide-2026/08-project-customer-support/</guid><description>&lt;h2 id="introduction-your-first-real-world-ai-agent"&gt;Introduction: Your First Real-World AI Agent!&lt;/h2&gt;
&lt;p&gt;Welcome to Chapter 8! Up until now, we&amp;rsquo;ve explored the theoretical foundations, core components, and setup of OpenAI&amp;rsquo;s open-sourced Agents SDK. We&amp;rsquo;ve discussed what makes an AI agent &amp;ldquo;agentic&amp;rdquo; and how to define its tools and persona. Now, it&amp;rsquo;s time to put all that knowledge into practice by building a fully functional, albeit simplified, customer support agent. This chapter marks a significant milestone: your first real-world project!&lt;/p&gt;</description></item><item><title>Chapter 9: Monitoring, Observability, and Debugging Agent Performance</title><link>https://ai-blog.noorshomelab.dev/openai-cs-agents-guide-2026/09-monitoring-debugging/</link><pubDate>Sun, 08 Feb 2026 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/openai-cs-agents-guide-2026/09-monitoring-debugging/</guid><description>&lt;h2 id="chapter-9-monitoring-observability-and-debugging-agent-performance"&gt;Chapter 9: Monitoring, Observability, and Debugging Agent Performance&lt;/h2&gt;
&lt;p&gt;Welcome to Chapter 9! By now, you&amp;rsquo;ve built, integrated, and deployed your OpenAI Customer Service Agents. That&amp;rsquo;s a huge achievement! But the journey doesn&amp;rsquo;t end with deployment. In the real world, agents need constant care and attention to ensure they&amp;rsquo;re performing optimally, handling user requests effectively, and not costing a fortune. This is where monitoring, observability, and debugging become your best friends.&lt;/p&gt;</description></item></channel></rss>