Toolify Toolify logo
open
Home AI News Build an AI Coding Agent from Scratch: Python Tutorial

Build an AI Coding Agent from Scratch: Python Tutorial

Updated on Oct 18,2025

Table of Contents

Interested in building AI-powered coding assistants? This tutorial will walk you through creating an AI coding agent from scratch using Python. This project focuses on demonstrating how AI agents work at a fundamental level, building a functional agent in just over 200 lines of code. It's an excellent learning opportunity for those who want to understand the inner workings of AI agents without relying on complex frameworks. Let's dive in!

Key Points

Learn to build an AI coding agent from scratch using Python.

The agent can read, list, and edit files through conversational interaction.

It leverages the Anthropic API (Claude) for AI conversational assistance.

The code is streamlined and avoids complex frameworks for clarity.

Key features include reading file contents, listing directory contents, and editing files.

The agent uses a chat loop for continuous interaction, driven by AI decisions.

Logging is incorporated to track all interactions within the agent.

The system prompt configures the AI to be concise, friendly, and act as a coding assistant.

Getting Started with Your AI Coding Agent

Understanding the AI Coding Agent

The AI coding agent uses the Anthropic API's Claude model to provide conversational AI that can read, list, and edit files.

The key capabilities and features are:

  • Read File: Reads the contents of a specified file.
  • List Files: Lists the files and directories within a given directory.
  • Edit File: Edits or creates files.

The agent operates in a chat loop, where it decides when to use tools or answer questions directly, using tool results to shape responses. All agent interactions are logged to agent.log.

This project has been created to demonstrate how AI coding agents work. This ensures that the code remains manageable and easy to grasp. By keeping the codebase concise, the mechanics of how the agent parses responses, executes tools, and maintains conversational context become much clearer.

Initial Setup: Cloning the GitHub Repository

To get started, clone the project's GitHub repository, where the source code lives, to follow along effectively.

The repository, daveebbelaar/single-file-ai-agent-Tutorial, contains all the files needed to build the agent. The repository and this video use the work of Francis Bisson, who initially created this repository as a means for others to get started easily with AI agents.

To get started cloning:

  1. Navigate to the project's GitHub repository.
  2. Click the Code button and copy the repository URL.
  3. Use git clone in your terminal to download the project files to your local machine. For example: git clone https://github.com/daveebbelaar/single-file-ai-agent-tutorial.git

Once cloned, open the project in your preferred IDE. VS Code or Cursor is preferable.

Setting Up Python and Dependencies

After cloning the repository, set up your Python environment to run the AI coding agent. This project requires Python 3.12 or higher and some dependencies. The video recommends using UV for dependency management.

  1. Install Python 3.12+: Ensure you have Python 3.12 or later installed.
  2. Install UV: UV, an extremely fast Python package and project manager, is a tool that will replace PIP.
  3. Using UV or PIP to install: To install dependencies, navigate to the project directory in your terminal and run: uv run main.py

UV streamlines the dependency installation process and ensures a fast, consistent environment.

Obtaining an Anthropic API Key

The AI coding agent is powered by the Anthropic API and Claude Sonnet 4.5 to function.

You'll need an API key to run the agent. Here's how to get one:

  1. Go to Anthropic Console: Navigate to the Anthropic console at console.anthropic.com.
  2. API Keys Section: Look for the API Keys option in the left menu.
  3. Create a Key: Follow the instructions to generate your API key.

Once you have the key, it will be necessary to store the API in your environment variable to connect the AI agent with Anthropic. Here is how it is done.

export ANTHROPIC_API_KEY="your-api-key-here"

Navigating the Project Files

The AI coding agent project is intentionally simple, containing only a few core files:

  • .env: Holds environment-specific variables for configuration.
  • .gitignore: Specifies intentionally untracked files that Git should ignore.
  • agent.log: Logs all interactions and operations performed by the AI agent.
  • LICENSE: Contains the licensing details for the project.
  • main.py: Contains the primary Python code for the AI coding agent.

Conclusion: Embarking on the AI Coding Journey

The Future of AI in Code

In conclusion, building an AI coding agent from scratch provides an excellent educational experience to learn and explore the inner functions of AI. With just over 200 lines of code, this provides a simple foundation for expanding AI coding abilities, giving you a basic but powerful way to interact with and modify your code environment.

As AI and machine learning continue to develop, AI coding assistants will become increasingly essential tools for developers. This tutorial acts as the basis that helps developers not only use but create future innovations with AI. To learn more, check out the GitHub repos and check out this other related video!

How to Use the AI Coding Agent

Running the AI Coding Agent

To start the AI coding agent, use the following command:

uv run main.py

This command initializes the AI agent and starts a conversational loop in the terminal, allowing you to interact with it directly.

Example Interactions

After starting the AI coding agent, the following interactions are all possible:

  1. List Files: List all files in this dir

  2. Read A File: What's in the main.py file?

  3. Have AI create another function Can you create another function to this?

  4. Empty File Can you now empty the file

Pros and Cons of Creating an AI Coding Agent from Scratch

👍 Pros

Deeper understanding of AI mechanics.

Full control over functionality and behavior.

Customizable to specific coding needs.

No reliance on external frameworks, simplifying debugging.

👎 Cons

Requires significant coding and debugging effort.

Time-consuming compared to using existing frameworks.

Limited features in basic implementation compared to sophisticated tools.

Not as easily scalable.

FAQ

What are the main uses of an AI coding assistant?
AI coding assistants can be used to debug code and explain errors, write new code or functions, refactor code for improvement, and navigate and understand project structures. They serve as a digital aid, increasing productivity and helping to maintain code standards.
Can the AI Coding Agent use the tools given without prompt?
No, the current version still requires the users to follow prompts.
Does the AI Coding Agent keep record of my session for history?
All activities completed by the Agent will be recorded in the agent.log file for traceability.

Related Questions

What are the key benefits of creating an AI coding agent from scratch?
Creating an AI coding agent from scratch provides a transparent view into how AI agents function. It offers greater control over the agent's behavior and features, enabling customization and optimization. Building from scratch helps developers thoroughly understand each component, leading to deeper insights and innovation in AI application.
What are the potential security implications and how do I keep them secure?
When building AI agents with direct file system access, security should always be prioritized. It’s essential to ensure that the AI agent can only access and modify files within a predefined scope to prevent unauthorized access. Authentication mechanisms and proper input validation can also reduce the risk of malicious commands being executed by the AI.
What other projects can I work on after finishing this one?
After completing this AI coding agent project, you can continue your coding journey with more options. Such as: building an AI resume assistant, create an Image Recognition tool and integrate it, or even a chatbot to manage your social media accounts
EdrawMax: AI-Powered Diagramming Software for Enhanced Productivity
AI Cold Email Personalization: A Free Tool Guide

Most people like

Related Articles
Top AI Tools
More Tools
Recommend
Resourse
Browse by Alphabet
Top 1000 AI Tools Directory
Read more
About
Contact Us
toolify
Toolify, The Best AI Websites & AI Tools Directory
English 简体中文 繁體中文 한국어 日本語 Português Español Deutsch Français Tiếng Việt

Copyright ©2026 toolify