Learn how to build agentic AI systems that reason, plan, and act autonomously using LLMs, memory, and tools. Explore single and multi-agent setups, guardrails, and N8N integrations to create intelligent, personalized, real-world solutions.

This video explains agentic AI, showing how agents use LLMs, memory, and tools for complex tasks and decision-making. It introduces Agentic RAG, key design patterns, real-world use cases, and frameworks like Azure AI Agent Service and Autogen.

Liam Ottley shares a beginner-friendly guide to building and monetizing AI agents, explaining core components like LLMs, prompts, tools, and memory. He demonstrates creating conversational and automated agents using no-code platforms, with real-world applications in support, lead generation, and research.

Learn how to use LangGraph to build reliable, autonomous AI agents with graph-based orchestration, memory, and human-in-the-loop controls. Through hands-on projects, you’ll master concepts like checkpoint memory, performance monitoring, and safe decision-making for complex workflows.

Tina Huang offers a beginner-friendly guide to building AI agents using both no-code and code-based tools, explaining key components like models, tools, memory, and guardrails. Through real-world examples and workflows, you’ll learn prompt engineering and how to design practical agents