Learn to build AI agents the LangGraph way! Build a toolbox of tools to help your agent interact with APIs, retrieve data from CSV files, and run Python code! Begin to build a single-agent system using nodes and edges to connect the LLM and tools in a controlled and methodical way.

Building agents the LangGraph way!

Agent toolbox: Wikipedia tool

Agent toolbox: stock data tool

Agent toolbox: Python tool

Agentic orchestration with LangGraph

Your first agent!

Agents as Graphs

Since the rise of AI agents, a handful of agentic design patterns have emerged, and you'll learn about two of the most popular: swarm (or decentralized) multi-agents and supervisor multi-agents. You'll see that LangGraph provides a whole host of functionality to design multi-agents tailored to your specific use case.

To tool or not to tool!

Conditional tool calls

One-line agents

Multi-agent frameworks

Another agent!

Supervisor agents

Wrap-up

LangGraph Multi-Agents

Design and build your own agents with LangGraph! LangGraph is a core part of the LangChain ecosystem, and it's used to build production-ready AI agents with a high degree of customizability. You'll use LangGraph to build an agentic assistant to gather information and stock performance data on Fortune 500 companies, and analyze it using visualizations! Discover state-of-the-art multi-agent architectures, including swarm (or decentralized) multi-agents and supervisor mult-agents. Become a builder of AI agent systems today!

<h2>Build AI Agents with LangGraph</h2>Design and build your own agents with LangGraph! LangGraph is a core part of the LangChain ecosystem, and it's used to build production-ready AI agents with a high degree of customizability. LangGraph allows developers to build agents as graphs with nodes and edges, which allows information flow and decision pathways to be carefully mapped out, and reduces the room for unexpected errors to creep in.<h2>Explore Emerging Multi-Agent Architectures</h2>Since the rise of AI agents, a handful of agentic design patterns have emerged, and you'll learn about two of the most popular: network (or decentralized) multi-agents and supervisor multi-agents. Manage multiple agents effectively by designing a supervisor agent to delegate tasks and encourage collaboration between the worker agents.<h2>Create Your Own Agentic Assistant</h2>You'll use LangGraph to build an agentic assistant to gather information and stock performance data on Fortune 500 companies, and analyze it using visualizations!<br><br>You'll see this agent progress from a simple single-agent system to a three-agent supervisor multi-agent! Join the growing number of AI builders and learn to design and build AI agents today!

Designing Agentic Systems with LangChain

Build powerful multi-agent systems by applying emerging agentic design patterns in the LangGraph framework.

Multi-Agent Systems with LangGraph

Curriculum Manager, DataCamp

The linear agent

Conditional edges

Conditional edges in practice

Let's practice!

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LangGraph Multi-Agents - To tool or not to tool!

To tool or not to tool!

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