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AI Agents in LangGraph

LangChain, a popular open source framework for building LLM applications, recently introduced LangGraph. This extension allows developers to create highly controllable agents. In this course you will learn to build an agent from scratch using Python and an LLM, and then you will rebuild it using LangGraph, learning about its components and how to combine them to build flow-based applications. Additionally, you will learn about agentic search, which returns multiple answers in an agent-friendly format, enhancing the agent’s built-in knowledge. This course will show you how to use agentic search in your applications to provide better data for agents to enhance their output. In detail: 1. Build an agent from scratch, and understand the division of tasks between the LLM and the code around the LLM. 2. Implement the agent you built using LangGraph. 3. Learn how agentic search retrieves multiple answers in a predictable format, unlike traditional search engines that return links. 4. Implement persistence in agents, enabling state management across multiple threads, conversation switching, and the ability to reload previous states. 5. Incorporate human-in-the-loop into agent systems. 6. Develop an agent for essay writing, replicating the workflow of a researcher working on this task. Start building more controllable agents using LangGraph!

状态:LangGraph
状态:Human Centered Design
中级项目小时

精选评论

MK

5.0评论日期:Jan 4, 2026

It was quite informative with clear explanation of the concept

EW

5.0评论日期:Sep 18, 2024

very interesting and inspiring work, also solidify my knowledge of llms.

CR

5.0评论日期:Oct 1, 2025

Very nice. However please check the Agentic Search. Is it really agentic search, it appeared to search using tavily search only

NS

5.0评论日期:May 28, 2025

I congratulate and thank you for conducting the course through direct practical work.

JM

5.0评论日期:May 6, 2025

Very informative project on LangGraph and getting started with AI Agents. Inspired a lot of great ideas and look forward to building AI Agents with LangChain and LangGraph.

AN

5.0评论日期:Nov 11, 2024

Great project! It provides a good starting point in the world of Agents with LangGraph. Now, I am eager to learn more and to implement my own agentic workflows.

NN

5.0评论日期:Jan 30, 2025

Great, spot-on content! This was a quick and easy-to-understand mini project that provides a solid overview of the world of agents and their possible implementations.

SJ

5.0评论日期:Jun 26, 2025

I easily and fully understood LangGraph and AI Agents with the lecture and the source code. This course is awesome!!!

KH

5.0评论日期:Apr 1, 2026

Excellent course! Here's my perspective, "LangChain is your bucket of Lego bricks. LangGraph is the spaceship you build that actually flies itself."

TR

5.0评论日期:Aug 6, 2025

Very engaging learning experience. A lot of content, it took me 3hrs to finish watching all these. Still I'll have to revisit.

所有审阅

显示:20/49

Marcello Belloli
4.0
评论日期:Nov 24, 2024
Nir Ness
5.0
评论日期:Jan 31, 2025
Steve Jobs
5.0
评论日期:Jun 27, 2025
Evan Mendenhall
5.0
评论日期:Jul 1, 2024
J Martin
5.0
评论日期:May 6, 2025
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5.0
评论日期:Nov 12, 2024
Kenny Ha
5.0
评论日期:Apr 2, 2026
Chandrashekar Ramamurthy
5.0
评论日期:Oct 2, 2025
Tarun Roy
5.0
评论日期:Aug 6, 2025
Nizami Sevindi
5.0
评论日期:May 29, 2025
Elise W.
5.0
评论日期:Sep 19, 2024
Manoj Kumar
5.0
评论日期:Jan 5, 2026
ANDRES VILLASEÑOR LECHUGA
5.0
评论日期:Jul 30, 2025
Benjamín Bas Peralta
5.0
评论日期:May 21, 2025
Udit Gupta
5.0
评论日期:Aug 19, 2025
SAVALIYA BHAGYESHKUMAR
5.0
评论日期:Jun 5, 2025
debobrata poddar
5.0
评论日期:Aug 29, 2024
Rafael Traldi Oliveira
5.0
评论日期:Aug 7, 2025
Sanjay Upadhyay
5.0
评论日期:Jul 20, 2024
Barry Hicks
5.0
评论日期:Jan 13, 2025