The Crutch Effect: How AI Tools Became A Crutch

Just like leaning on a physical crutch for too long can weaken your muscles, relying too much on AI can weaken your coding abilities. AI tools offer numerous benefits:

• Efficiency: They speed up repetitive tasks.
• Assistance: They help with syntax and suggest code snippets.
• Learning Aid: They can explain complex concepts.

However, these advantages can lead to over-reliance. Consider Jamie, a developer who uses an AI assistant for almost every coding task. One day, the AI service is unavailable. Jamie struggles to write even basic functions, realizing that relying on AI has dulled their coding instincts.

The Birth of The Crutch Effect

Reflecting on Jamie’s struggle, it became clear that this wasn’t an isolated incident. Many developers are experiencing similar challenges. The convenience of AI tools led to an unintended consequence: a decline in fundamental coding skills.

The Crutch Effect refers to the dependency that forms when developers rely too heavily on AI assistance, leading to:

• Coding Skills Atrophy: Diminished ability to write code independently.
• Shallow Understanding: Missing out on the ‘why’ and ‘how’ behind the code.

Finding Balance: Using AI Without Over-Reliance

It’s not about ditching AI entirely but using it wisely. Here are my strategies for healthier AI use.

• Set Boundaries: Use AI for suggestions, but write the core logic yourself.
• Active Learning: When AI provides a solution, take time to understand it fully.
• Practice Regularly: Allocate time to code without any AI assistance.

Think of AI tools as helpful assistants, not as replacements for your thinking. Let AI handle the grunt work—like generating boilerplate code or reminding you of syntax—but keep the critical thinking and problem-solving to yourself.

Suppose you’re building a web application and must set up a basic Express server in Node. You might use an AI tool to scaffold the initial setup:

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const express = require('express');
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const app = express();
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app.listen(3000, () => {
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  console.log('Server is running on port 3000');
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});

That’s fine for saving time on repetitive tasks. But when it comes to designing your API endpoints, handling business logic, or implementing security measures, write that code yourself. This ensures you understand every part of your application.

By setting boundaries, you prevent over-reliance on AI and keep your skills sharp. You get the efficiency benefits without sacrificing your growth as a developer.

AI should be a tool in your toolkit, not the entire toolbox. Don’t just copy and paste AI-generated code. Dive into it. Understand how and why it works. This turns AI from a crutch into a learning tool.