<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Gemini CLI on The Coders Blog</title><link>https://thecodersblog.com/tag/gemini-cli/</link><description>Recent content in Gemini CLI on The Coders Blog</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Sun, 10 May 2026 15:59:05 +0000</lastBuildDate><atom:link href="https://thecodersblog.com/tag/gemini-cli/index.xml" rel="self" type="application/rss+xml"/><item><title>AI Agents: Gemini CLI Introduces Subagents</title><link>https://thecodersblog.com/gemini-cli-subagents-2026/</link><pubDate>Sun, 10 May 2026 15:59:05 +0000</pubDate><guid>https://thecodersblog.com/gemini-cli-subagents-2026/</guid><description>&lt;p&gt;For years, the promise of AI agents has been to offload complex, often tedious tasks, freeing up human cognitive bandwidth. While early iterations showcased impressive capabilities, they often struggled with context management and the sheer scope of real-world problems. Imagine trying to ask a single, monolithic AI to refactor a massive legacy codebase, debug a complex network issue, and then draft a detailed technical proposal – all in one go. The result is invariably a confused AI, a deluge of irrelevant information, or a spectacular failure to execute. The Gemini Command Line Interface (CLI), with its recent introduction of &lt;em&gt;subagents&lt;/em&gt; in version 0.38.1 (released April 15, 2026), is making a bold stride towards solving this very challenge by injecting modularity and specialization into the AI agent paradigm. This isn&amp;rsquo;t just an incremental update; it&amp;rsquo;s a fundamental shift in how we can architect and leverage AI for command-line workflows.&lt;/p&gt;</description></item></channel></rss>