Building AI Agents with LangChain and LangGraph: Part 1 › Introduction
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This is the first article in a series exploring how to build intelligent agents with LangChain and LangGraph. We'll start with the fundamental concepts that form the foundation of all agent-based systems.
Modern AI applications often need to do more than just generate text - they need to take actions in the real world. LLM workflows enable language models to interact with external systems by giving them access to tools and functions.
In this foundational guide, you'll learn the core building blocks:
- How to connect language models to external tools
- Design robust tool schemas that models can understand
- Handle tool responses and create reliable workflows
- Build systems that feel natural and intelligent
Let's start by setting up our environment and understanding these essential concepts.
Creating a Customer Support Agent
Let's design a straightforward agent capable of automatically drafting responses to customers and categorizing the responses.