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)
Build your first practical AI agent with LangChain using the latest `create_agent` API. In this hands-on Python tutorial, we create a customer-support agent that can check an order status, verify refund eligibility, call the correct tools, and return structured output. You will learn: ✅ What makes an AI agent different from a chatbot ✅ Why `create_agent` is the current LangChain agent API ✅ How to create tools using typed Python functions ✅ How the model selects and calls tools ✅ How to return validated structured output with Pydantic ✅ How the LangChain agent loop works ✅ Where middleware, guardrails, and human approval fit ✅ What must change before using an agent in production The example uses mock order data so you can understand the complete flow safely. In a production application, the tools can connect to databases, REST APIs, order-management platforms, or internal business systems. This video is designed for Python developers, AI beginners, and anyone learning how to build practical agentic applications. Subscribe to Naveen TechHub for practical tutorials on AI engineering, cloud, automation, Python, and modern software development. If this video helped you, please like, share, and comment with the next AI-agent use case you want to see. #LangChain #AIAgents #Python #GenerativeAI #AgenticAI #LangGraph #PythonTutorial #AITutorial #LLM #MachineLearning #AIEngineering #NaveenTechHub