AI Agents For Beginners (A to Z) In 18 minutes

In this video, we break down the essential components needed to build AI agents and applications, and how to integrate them into your business. Whether you're a beginner or an experienced developer, this guide will help you understand the interconnected parts of AI systems, making it easier for you to create your own AI solutions. What you'll learn: 🧠 Understanding Large Language Models (LLMs) and their role as the brain of AI agents. 📝 Crafting effective system prompts to guide your AI agent's behavior. 🔄 Differentiating between AI workflows and AI agents. 📚 Implementing RAG (Retrieval-Augmented Generation) for context-aware responses. 🔧 Utilizing function tools to enhance your AI agent's capabilities. 🔗 Connecting everything with agent orchestration frameworks. 📊 Monitoring and optimizing with LLM observability tools. 🌐 Setting up APIs and cloud services for scalability and accessibility. 💻 Designing user-friendly front ends for seamless interaction. Don't forget to like, subscribe, and hit the bell for more insights on building AI agents and applications! 🔗 Connect with me on LinkedIn: https://www.linkedin.com/in/jonathan-miz/ 👉🏼 Related Videos: https://youtu.be/RGEJhcWdXR4 https://youtu.be/78x1dB4poaE https://youtu.be/eIvhkcanK_4 #AI #AIAgents #LLM #TechStack #NoCode #Coding #AIApplications Chapters: 0:00 Introduction 0:43 What's an LLM 1:26 System prompts 2:35 AI Agents VS AI Workflows? 4:40 RAG - Retrieval-augmented generation 9:22 Function Tools 12:32 Agent orchestration 13:15 LLM Observibility 14:17 API 14:56 Cloud Services 15:30 Front end 16:16 Summary