How to Build an AI Agent from Scratch with LangChain and OpenAI (Beginner’s Guide)

7/3/20251 min read

Ever wondered how to build an AI agent like the ones powering ChatGPT or smart assistants? In this beginner-friendly guide, we’ll walk you through the step-by-step process to build your first AI agent using LangChain and OpenAI.

Whether you're a solo developer, AI enthusiast, or startup founder, this post gives you the foundational knowledge to build and run an intelligent agent with just a few lines of Python.

What Is an AI Agent?

An AI agent is a program powered by a language model (like OpenAI’s GPT) that can:

Accept and interpret user input
Respond intelligently based on context
Be extended with tools, memory, or APIs

LangChain provides the perfect toolkit to build one quickly and modularly.

What You’ll Need

Python 3.9+
An OpenAI API key from platform.openai.com
Basic Python coding skills

Step 1: Install Required Libraries

Step 2: Set Up Your OpenAI-Powered LLM

We'll start by setting up a basic ChatOpenAI instance using LangChain:

Step 3: Build a Basic Agent Using ConversationChain

LangChain provides ConversationChain, a simple wrapper that lets your model behave like a chat assistant.

Step 4: Run Your AI Agent

Now you can chat with your agent from your terminal:

It will remember the context of the conversation within the same session.

Add a Simple Prompt Template

You can define a custom system message to guide the agent’s tone and personality:

Sample Output

Final Thoughts

Congrats! You just built a fully functional AI agent using LangChain and OpenAI. While it’s simple, this agent can now be extended with:

Memory (buffer, summary, vector)
Tools (web search, APIs)
Actions (code execution, file writing)
Interfaces (chat UIs, voice, SMS)

This is step 1 in your agent journey. In the next blog, we’ll show you how to add memory so your agent doesn’t forget past conversations.