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AI Agents in LangGraph

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Dear learner,

We’re excited to introduce another short course on agentic AI: AI Agents in LangGraph, created in collaboration with LangChain founder Harrison Chase, and Tavily founder Rotem Weiss.

LangGraph is an open-source framework that allows developers to create highly controllable agents. In this course, you will build an agent using Python and an LLM and then rebuild it using LangGraph, while learning about its components and how to combine them to build flow-based applications.

Additionally, you will learn how to use agentic search in your applications to provide better data for agents to enhance their output.

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In detail:

Build an agent from scratch, and understand the division of tasks between the LLM and the code around the LLM.
Implement the agent you built using LangGraph.
Learn how agentic search retrieves multiple answers in a predictable format, unlike traditional search engines that return links.
Implement persistence in agents, enabling state management across multiple threads, conversation switching, and the ability to reload previous states.
Incorporate human-in-the-loop into agent systems.
Develop an agent for essay writing, replicating the workflow of a researcher working on this task.

Start building more controllable agents using LangGraph.

Details

  • Learn about LangGraph’s components and how they enable the development, debugging, and maintenance of AI agents.
  • Integrate agentic search capabilities to enhance agent knowledge and performance.
  • Learn directly from LangChain founder Harrison Chase and Tavily founder Rotem Weiss.

https://learn.deeplearning.ai/courses/building-your-own-database-agent

Videos