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LangGraph 101: Building Stateful Multi-Agent AI Applications

Agenda

Building Smarter AI Multi-Agent Applications with LangGraph

Want to take your AI projects to the next level? Join us for an engaging webinar where we’ll dive into LangGraph and LangChain, showing you how to build smarter, stateful multi-agent AI systems. Learn how to use Large Language Models to create agents that do more than answer questions—they plan, execute, and adapt to complex tasks autonomously.

We’ll cover the “Plan-and-Execute” paradigm and compare it with traditional ReAct agents, helping you understand where each approach shines. You’ll learn how to set up your development environment, define tools, manage agent states, and even construct graphs using LangGraph—all with plenty of practical insights and real-world examples.

Whether you’re just starting or already working with multi-agents, this webinar will give you the skills and inspiration you need to create sophisticated, dynamic AI systems that can think ahead. Let’s unlock the true potential of LangGraph together and take your AI capabilities to the next level.

What You’ll Learn:

  • Understand the core principles of LangGraph and its agentic architectures.
  • Design and build intelligent agents using LangChain and LangGraph.
  • Learn to manage agent states effectively, including planning, executing, and adapting.
  • Develop multi-agent AI systems that are efficient, stateful, and ready for real-world challenges.

Who Should Attend:

  • AI developers and tech professionals eager to deepen their knowledge of intelligent agents and AI systems.
  • Data scientists interested in building autonomous workflows and understanding state management in LangGraph.
  • Software engineers looking to integrate Large Language Models into more complex, capable systems.
  • Anyone fascinated by the potential of AI and curious about creating advanced agents that adapt, plan, and execute autonomously.
Building AI Multi-Agents with LangGraph
Syed Hyder Ali Zaidi

Azure Certified Data Scientist at Data Science Dojo

Hyder is an Azure-Certified Data Scientist at Data Science Dojo. He specializes in working with LLMs (Language Model Models) and computer vision services. Hyder has hands-on experience in developing projects that utilize LLMs for Natural Language Processing (NLP) tasks and applying computer vision techniques for visual data analysis.

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