Learn how to build and deploy production-ready AI agents using AWS Bedrock AgentCore! In this hands-on tutorial, I'll show you how to create a LangGraph agent with web search capabilities and deploy it to AWS Bedrock Agentcore Runtime in just minutes. 📺 What You'll Learn: - What is Amazon Bedrock AgentCore and why it's a game-changer - Building a LangGraph agent with DuckDuckGo search integration - Testing locally with LangGraph Studio - One-command deployment to AWS cloud - Production monitoring and observability 🛠️ Tech Stack: - AWS Bedrock AgentCore (Preview) - LangChain & LangGraph - Python - DuckDuckGo Search API - AWS Lambda, ECR, CodeBuild 💡 Key Features of AgentCore: ✅ Works with ANY agent framework (LangGraph, LangChain, CrewAI, etc.) ✅ Compatible with ANY foundation model (not just Bedrock) ✅ Serverless execution with complete session isolation ✅ Built-in memory management and tool integration ✅ Production-ready logging and monitoring 🔗 Resources: - AWS Bedrock AgentCore Docs: - LangGraph Documentation: 📋 Prerequisites: - AWS Account with CLI configured - Python + - Basic understanding of LangChain/LangGraph Have questions? Drop them in the comments below! 💬