<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>AI/ML Development on Rachid Youven Zeghlache</title><link>https://youvenz.github.io/tags/ai/ml-development/</link><description>Recent content in AI/ML Development on Rachid Youven Zeghlache</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Wed, 04 Mar 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://youvenz.github.io/tags/ai/ml-development/index.xml" rel="self" type="application/rss+xml"/><item><title>Tool Calling Explained: Turn Your LLM into an AI Agent</title><link>https://youvenz.github.io/blog/2026-03-04-tool-calling-explained-turn-your-llm-into-an-ai-agent/</link><pubDate>Wed, 04 Mar 2026 00:00:00 +0000</pubDate><guid>https://youvenz.github.io/blog/2026-03-04-tool-calling-explained-turn-your-llm-into-an-ai-agent/</guid><description>&lt;h2 id="tool-calling-explained--how-to-turn-your-llm-into-an-ai-agent-that-actually-does-things"&gt;Tool Calling Explained — How to Turn Your LLM into an AI Agent That Actually Does Things&lt;/h2&gt;
&lt;p&gt;Out-of-the-box LLMs can&amp;rsquo;t check your calendar, pull live weather data, or query your database. They&amp;rsquo;re brilliant conversationists trapped in a sensory deprivation chamber, completely isolated from the real world. The result? You get impressive prose about &lt;em&gt;what&lt;/em&gt; to do, but zero ability to actually &lt;em&gt;do&lt;/em&gt; it.&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;Tool calling&lt;/strong&gt; (also called function calling) changes everything. It&amp;rsquo;s the bridge that transforms a chatbot into an agent—an LLM that can invoke external functions and APIs. Yet most explanations overcomplicate it.&lt;/p&gt;</description></item></channel></rss>