🚀 What is LangGraph? LangGraph is a framework that helps you build complex AI workflows using graphs, where each node represents a step (or “agent”) in the process. It’s built on top of LangChain and is ideal for managing multi-agent systems. Think of it as building an AI assembly line where each step (agent or human) contributes something. 🔍 Key Concepts You'll Learn 🔸 1. AI Workflows with LangGraph Learn how to design multi-step AI processes (e.g., document summarization → sentiment analysis → decision). Each step is a node in a graph (like a flowchart), and the data flows through it. You’ll orchestrate models, tools, and logic to create real apps, not just one-shot prompts. 🔸 2. Agents in LangGraph Agents are autonomous decision-makers that can choose tools, run tasks, or call other models. You’ll learn to configure agents that can: Search the web Summarize data Make decisions based on outcomes It’s like building a mini-team of AI workers with specialized roles. 🔸 3. Human-in-the-Loop (HITL) Learn how to bring humans into the workflow when AI needs approval, correction, or supervision. Add review points where humans check the AI’s output before moving forward. HITL is essential in high-stakes tasks like legal analysis, education, or customer support. ✅ What You’ll Build (Beginner-Friendly Outcome) A LangGraph-powered app with multiple agents doing different tasks A workflow that pauses for human review before taking the next step A realistic, production-grade AI pipeline you can deploy or expand 💡 Why It Matters You move from single prompts to full AI systems Learn how real-world AI applications are built—with structure, review, and intelligent flow Gain hands-on experience with agent orchestration, a key trend in 2025+ AI development