Course Project Orientation

In this course, we are moving beyond simple AI chatbots. You will learn to use Codex, a "repo-native" agent. This means the AI doesn't just look at a single snippet of code; it understands how an entire project (a repository) fits together. Throughout this path, you will learn to configure Codex to plan tasks, fix bugs, and resume work exactly where it left off.

To learn these skills, we need a real project to work on. We will be using a version of Excalidraw, a popular open-source digital whiteboard tool. It is a modern, complex application with many files, making it the perfect playground for testing our AI agent’s abilities.

At the heart of this agent is GPT-5-Codex, a specialized version of OpenAI’s language model. Unlike general-purpose models, GPT-5-Codex is trained on real engineering tasks and workflows. This allows it to:

• Understand Project Context: It doesn't just see the file you are in; it understands how files interact.
• Perform Engineering Work: It can generate code, refactor complex logic, write tests, and fix bugs.
• Handle Multi-step Instructions: You can give it high-level goals in plain English, and it will plan the necessary file changes.

To use Codex CLI on your own machine, you would typically follow these steps:

1. Install Codex CLI:

   npm install -g @openai/codex

   If you encounter permission errors, it’s best to use a Node version manager like nvm.

2. Set your OpenAI API key:

   export OPENAI_API_KEY="your-api-key"

   For persistent access, you can add this line to your shell configuration file (e.g., ~/.bashrc or ~/.zshrc), or place it in a .env file in your project directory.

3. Start Codex:

   codex

However, for the course, everything is already installed and configured for you—you just need to run codex to start the agent.

In the CodeSignal IDE, you will interact with Codex primarily through a Command-Line Interface (CLI). While Codex is available as a web assistant or editor extension, the CLI is the most direct way to use it for real-world automation and session management.

Everything is pre-installed and pre-configured for you. For Codex to work effectively, you must run it from the root directory of your project. This ensures the agent has access to all files, configuration scripts, and the full context of your application. If you run codex from a subdirectory, the agent’s visibility is effectively limited to that subtree, which can lead to incomplete repo maps, missed references, or less accurate plans.

When you run Codex commands, the agent analyzes your request, proposes a plan, and shows you a preview of changes. You stay in control, deciding whether to accept, modify, or reject the suggestions.

To get the best results, remember to be specific: instead of saying "Fix the code," say "Fix the crash in the renderCanvas function when the input is null."