Learn how to build real-world AI agents using frameworks like LangChain, LangGraph, CrewAI, and AutoGen. This playlist covers agent architectures, workflows, tool calling, memory, and real-world use cases — from beginner to advanced. Perfect for AI engineers, developers, and system design learners. #AIAgents #GenerativeAI #LangChain #AIEngineering
Curated by: Naveen Tech Hub (38 videos)
In this beginner-friendly Naveen TechHub session, learn how Agentic AI frameworks help connect LLMs with tools, memory, workflows, retrieval, state, and application logic. We start with the basics: • Why Agentic AI frameworks are needed • What makes an AI agent different from a simple LLM call • Code-based vs no-code / low-code approaches • Agno, LangChain, LangGraph, CrewAI, Google ADK, and OpenAI Agents SDK • Where each framework fits • LangChain as an abstraction and orchestration layer • Simple company chatbot architecture • RAG flow with retrievers and company documents • LangChain vs LangGraph vs LangSmith • Python modules, packages, functions, methods, classes, objects, and imports • First practical LangChain model call • How to move from a basic LLM app toward a real AI agent This video is designed for beginners, developers, AI/ML engineers, and anyone starting with Agentic AI. By the end, you should clearly understand the foundation required before building tool-using and stateful AI agents. Next video: Build Your First AI Agent with LangChain Tools Subscribe to Naveen TechHub for practical AI, GenAI, Agentic AI, Cloud, DevOps, and software engineering tutorials. #AgenticAI #LangChain #LangGraph #CrewAI #Agno #OpenAI #GoogleADK #GenerativeAI #AIagents #Python #RAG #NaveenTechHub