<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Tmux on AI VOID</title><link>https://ai-blog.noorshomelab.dev/tags/tmux/</link><description>Recent content in Tmux on AI VOID</description><generator>Hugo</generator><language>en</language><lastBuildDate>Fri, 20 Mar 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://ai-blog.noorshomelab.dev/tags/tmux/index.xml" rel="self" type="application/rss+xml"/><item><title>Beyond Single Agents: Orchestrating Multi-Agent Workflows and AI-Discoverable Skills</title><link>https://ai-blog.noorshomelab.dev/cli-first-ai-systems-guide-2026/orchestrating-multi-agent-workflows/</link><pubDate>Fri, 20 Mar 2026 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/cli-first-ai-systems-guide-2026/orchestrating-multi-agent-workflows/</guid><description>&lt;h2 id="introduction"&gt;Introduction&lt;/h2&gt;
&lt;p&gt;Welcome back, intrepid command-line explorer! In previous chapters, we&amp;rsquo;ve journeyed into the exciting world of CLI-first AI systems, understanding how a single AI agent can perceive, reason, and act directly within your terminal. We&amp;rsquo;ve seen how these agents can automate tasks, interact with shell tools, and even generate code. Pretty cool, right?&lt;/p&gt;
&lt;p&gt;But what if a task is too big, too complex, or requires different specializations that a single agent can&amp;rsquo;t easily handle alone? Imagine a team of highly skilled individuals, each with their own expertise, collaborating to achieve a grander goal. This is precisely the power of &lt;strong&gt;multi-agent workflows&lt;/strong&gt;. In this chapter, we&amp;rsquo;ll dive into how to orchestrate multiple AI agents to tackle more intricate challenges, turning your terminal into a collaborative AI hub.&lt;/p&gt;</description></item></channel></rss>