Modular Code and AI Agents
AI coding agents have a superpower and a limitation. They can generate, explain, and modify code remarkably well — but only when they can hold the relevant code in their context window. This makes modularity not just good practice, but essential for effective AI collaboration.
What Is a Module?
A module is a self-contained unit of code with a clear purpose. It might be a single file, a class, or a collection of related functions. The key characteristic is that you can describe what it does in one sentence.
"This module handles all database connections." "This module validates user input." "This module formats data for display."
If you can't summarize a module in one sentence, it's probably doing too much.
Why Modularity Helps AI
When you paste a 500-line file into an AI chat and ask for help, the AI must understand all of it to make changes safely. It might miss connections between distant parts of the code. It might make changes that break something it didn't fully grasp.
But when you share a focused 30-line module, the AI can understand it completely. It sees all the inputs, outputs, and logic. It can make precise changes with confidence.
Instead of "Fix my 500-line file," try "Here's my 30-line data fetching module. Add retry logic."
Structuring Projects for AI
Think about how you'll work with AI when organizing your code:
- One file per concern: Keep data access, business logic, and presentation in separate files.
- Clear interfaces: Each module should have obvious inputs and outputs.
- Minimal dependencies: Modules that depend on many other modules are harder to work with in isolation.
When you need to modify something, you can share just the relevant module with AI, get focused help, and integrate the changes back.
Testing Benefits
Modular code isn't just AI-friendly — it's test-friendly too. You can test each module independently, with fake inputs, without running your entire application. This makes bugs easier to find and fix.
The Rule of Thumb
If you're struggling to explain a piece of code to AI (or to yourself), that's a signal to split it up. Smaller, focused modules lead to better AI assistance and cleaner code overall.