<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Tool Use on AI VOID</title><link>https://ai-blog.noorshomelab.dev/tags/tool-use/</link><description>Recent content in Tool Use on AI VOID</description><generator>Hugo</generator><language>en</language><lastBuildDate>Wed, 20 May 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://ai-blog.noorshomelab.dev/tags/tool-use/index.xml" rel="self" type="application/rss+xml"/><item><title>Core Components: LLMs, Tools, and Memory Essentials</title><link>https://ai-blog.noorshomelab.dev/ai-agent-frameworks-2026/core-components-llms-tools-memory/</link><pubDate>Fri, 20 Mar 2026 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/ai-agent-frameworks-2026/core-components-llms-tools-memory/</guid><description>&lt;p&gt;Welcome back, aspiring AI architect! In the previous chapter, we embarked on an exciting journey into the world of AI agents, understanding their potential to revolutionize how we interact with technology. We learned that agents are more than just chatbots; they are intelligent entities capable of perceiving, planning, acting, and adapting to achieve specific goals.&lt;/p&gt;
&lt;p&gt;But how do these agents actually &lt;em&gt;work&lt;/em&gt;? What are the fundamental building blocks that empower them to perform complex tasks? That&amp;rsquo;s precisely what we&amp;rsquo;ll uncover in this chapter. Think of it as peeking under the hood of a sophisticated machine. We&amp;rsquo;ll explore the three indispensable components that form the bedrock of any modern AI agent:&lt;/p&gt;</description></item><item><title>Equipping Your Agent: Integrating and Using External Tools</title><link>https://ai-blog.noorshomelab.dev/agentic-ai-guide-2026/agent-tool-usage/</link><pubDate>Fri, 20 Mar 2026 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/agentic-ai-guide-2026/agent-tool-usage/</guid><description>&lt;h2 id="equipping-your-agent-integrating-and-using-external-tools"&gt;Equipping Your Agent: Integrating and Using External Tools&lt;/h2&gt;
&lt;p&gt;Welcome back, aspiring AI architect! In our previous chapters, we delved into the foundational concepts of autonomous AI agents, understanding their core components like planning and reasoning. We learned how an agent can &lt;em&gt;think&lt;/em&gt; about a problem, break it down, and even strategize. But what good is all that brilliant thinking if an agent can&amp;rsquo;t &lt;em&gt;act&lt;/em&gt; in the real world? It&amp;rsquo;s like having a brilliant chef who can plan the perfect meal but has no kitchen or ingredients!&lt;/p&gt;</description></item><item><title>Chapter 4: Tool Use &amp;amp; Function Calling: Extending LLM Capabilities</title><link>https://ai-blog.noorshomelab.dev/applied-agentic-ai-2026-guide/tool-use-function-calling/</link><pubDate>Fri, 16 Jan 2026 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/applied-agentic-ai-2026-guide/tool-use-function-calling/</guid><description>&lt;h2 id="chapter-4-tool-use--function-calling-extending-llm-capabilities"&gt;Chapter 4: Tool Use &amp;amp; Function Calling: Extending LLM Capabilities&lt;/h2&gt;
&lt;p&gt;Welcome back, future Applied AI Engineer! In our previous chapters, we mastered foundational programming, system thinking, and the art of crafting effective prompts to guide Large Language Models (LLMs). We learned how LLMs are incredible text generators, capable of understanding and producing human-like language. But what if an LLM needs to do more than just talk? What if it needs to &lt;em&gt;act&lt;/em&gt; in the real world, fetch live data, or perform calculations beyond its inherent knowledge?&lt;/p&gt;</description></item><item><title>Unleashing AI Agents: Building Smart, Automated Systems</title><link>https://ai-blog.noorshomelab.dev/triggerdev-v4-guide-2026/unleashing-ai-agents/</link><pubDate>Wed, 20 May 2026 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/triggerdev-v4-guide-2026/unleashing-ai-agents/</guid><description>&lt;h2 id="introduction"&gt;Introduction&lt;/h2&gt;
&lt;p&gt;Welcome to Chapter 7! In the rapidly evolving world of software, AI agents are becoming indispensable for automating complex, multi-step tasks that require reasoning, planning, and interaction with external tools. Imagine a system that can understand a user&amp;rsquo;s request, break it down into smaller problems, use various tools (like APIs or databases) to gather information, and then formulate a coherent response or take action—all without constant human supervision. That&amp;rsquo;s the power of AI agents.&lt;/p&gt;</description></item><item><title>Building Your First Agent: A Hands-On Autonomous System Project</title><link>https://ai-blog.noorshomelab.dev/agentic-ai-guide-2026/building-autonomous-agent-project/</link><pubDate>Fri, 20 Mar 2026 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/agentic-ai-guide-2026/building-autonomous-agent-project/</guid><description>&lt;h2 id="introduction"&gt;Introduction&lt;/h2&gt;
&lt;p&gt;Welcome, aspiring agent builder! In this chapter, we&amp;rsquo;re moving from theory to practice. You&amp;rsquo;ve explored the fascinating world of autonomous AI agents, delving into their core components like planning, reasoning, tool usage, and memory systems. Now, it&amp;rsquo;s time to get your hands dirty and build your very first functional AI agent.&lt;/p&gt;
&lt;p&gt;Our goal for this chapter is to construct a simple, yet powerful, &amp;ldquo;research assistant&amp;rdquo; agent. This agent will be capable of understanding a query, deciding if it needs external information, using a web search tool to find that information, and then synthesizing a coherent answer. This project will solidify your understanding of how these theoretical concepts translate into practical code, boosting your confidence in designing and implementing your own intelligent systems.&lt;/p&gt;</description></item><item><title>Chapter 14: Hands-On Project: Building a Smart Research Assistant Agent</title><link>https://ai-blog.noorshomelab.dev/applied-agentic-ai-2026-guide/project-research-assistant/</link><pubDate>Fri, 16 Jan 2026 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/applied-agentic-ai-2026-guide/project-research-assistant/</guid><description>&lt;h2 id="chapter-14-hands-on-project-building-a-smart-research-assistant-agent"&gt;Chapter 14: Hands-On Project: Building a Smart Research Assistant Agent&lt;/h2&gt;
&lt;p&gt;Welcome, aspiring Applied AI Engineer! In our journey so far, we&amp;rsquo;ve explored the foundational concepts of AI, Large Language Models (LLMs), prompt engineering, tool use, Retrieval-Augmented Generation (RAG), and the nascent world of agentic AI. Now, it&amp;rsquo;s time to bring these pieces together and build something truly functional and exciting: a Smart Research Assistant Agent.&lt;/p&gt;
&lt;p&gt;This chapter is your opportunity to put theory into practice. You&amp;rsquo;ll learn to design and implement a multi-agent system capable of understanding a research query, searching for information online, synthesizing findings, and presenting a coherent summary. We&amp;rsquo;ll leverage a modern agentic framework to orchestrate our agents, managing their states and interactions. Get ready to write some code, solve problems, and witness the power of AI agents in action!&lt;/p&gt;</description></item><item><title>Chapter 16: Hands-On Project: Building a Collaborative Multi-Agent System</title><link>https://ai-blog.noorshomelab.dev/applied-agentic-ai-2026-guide/project-collaborative-multi-agent/</link><pubDate>Fri, 16 Jan 2026 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/applied-agentic-ai-2026-guide/project-collaborative-multi-agent/</guid><description>&lt;h2 id="chapter-16-hands-on-project-building-a-collaborative-multi-agent-system"&gt;Chapter 16: Hands-On Project: Building a Collaborative Multi-Agent System&lt;/h2&gt;
&lt;p&gt;Welcome back, future Applied AI Engineer! In previous chapters, you&amp;rsquo;ve mastered individual AI agents, equipped them with tools, and given them memory. You&amp;rsquo;ve seen how a single intelligent agent can tackle complex tasks. But what if we could harness the power of &lt;em&gt;multiple&lt;/em&gt; specialized agents, allowing them to collaborate, brainstorm, and even debate to solve problems far more effectively?&lt;/p&gt;
&lt;p&gt;That&amp;rsquo;s precisely what this chapter is about! We&amp;rsquo;re diving into the exciting world of &lt;strong&gt;Multi-Agent Systems&lt;/strong&gt;. You&amp;rsquo;ll embark on a hands-on project to build a system where several AI agents work together to achieve a common goal, mimicking a real-world team. This will solidify your understanding of agent orchestration, communication patterns, and how to design AI-driven workflows that leverage collective intelligence.&lt;/p&gt;</description></item></channel></rss>