Agentic Design | Artificial Intelligence | Application Development
Building powerful LLM agents within constraints.
In this article we’ll explore “LangGraph”, a cutting-edge tool for making LLM agents that are actually useful.
First we’ll review what an “LLM agent” is, a few popular agentic design approaches, and some of their practical shortcomings. We’ll then discuss how LangGraph can be used to address these shortcomings to make more useful and maintainable agents.
Once we understand why LangGraph exists, we’ll explore the technology practically through something called a “State Graph”. We’ll use this state graph to build an agent which is capable of performing a complex task which requires the agent to deal with natural conversation, hard rules, and application logic. This will serve as a demonstration of how robust and customizable LangGraph agents are.
By the end of this article you’ll understand why LangGraph exists, why it’s important, and how to use it within your own projects.
Who is this useful for? Anyone who wants to form a complete understanding of the state of the art of AI. This article will be particularly interesting to those who are…