I Used AI to Automate My Coding Tasks: A Practical Guide

Let’s be honest, we’ve all been there. Staring at the screen, knowing you have to write yet another unit test, debug a finicky CSS layout, or churn out boilerplate code. It’s the necessary “eat your vegetables” part of being a developer. But what if you could get a little help? That’s where I brought in my AI assistants.

As a developer, I’ve started using AI tools to offload the repetitive, time-consuming parts of my job, and it’s been a game-changer. Here’s a no-fluff guide to how I’m doing it.

Image From UnSplash

My AI Toolkit

I don’t stick to just one. Different models have different strengths. My go-to’s are:

Comparison between the AI toolkit I used

✨ Tip: Try pairing the same prompt across two AIs. Sometimes, Claude gives a cleaner explanation, while ChatGPT provides more usable code snippets.

⚙️ 1. Writing React Components from Scratch
It starts with a clear, structured prompt. AI can generate robust, production-ready code — if you ask correctly.
🧪 Prompt Example:

“Create two React v17 functional components for a weather widget. The first shows today’s weather with temperature (toggle between °F and °C using Local Storage), a weather icon, and city name. The second shows a compact 5-day forecast. Both should be reusable and exportable.”

✅ AI Output Highlights:

• Uses useEffect, useState, and localStorage
• Fetches weather data via an API (like OpenWeatherMap)
• Provides responsive layout using Tailwind CSS (when requested)

🪲 2. Debugging Runtime and Dev Mode Errors
When starting the dev server, you might hit errors like “axios is not defined” or “missing import.” Instead of digging through StackOverflow, I now throw these straight to AI.

🔍 Prompt Example:

“When starting my React app in dev mode, I get axios is not defined error in my WeatherToday.jsx component. Here’s the code. Can you help fix it?”

💡 AI Suggestion:

• Identified missing import axios from ‘axios’;
• Also pointed out where the API key was hardcoded and recommended using .env for better security

🧪 3. Writing Unit Tests Using Jest
Once the components are working, I ask AI to generate unit tests using Jest, the most popular React testing framework.

🧪 Prompt Example:

“Write Jest unit tests for the WeatherToday React component. Test temperature toggle logic, localStorage persistence, and API error handling.”

✅ Output Included:

• Unit tests using @testing-library/react
• Mocks for axios and localStorage
• Edge case handling (e.g., invalid API response)

🎯 Pro Tip: If AI writes your components, ask it to write the tests in the same session — bugs become easier to spot early.

🎨 4. Styling Components with Tailwind CSS
Early UI prototypes can look dull, so I use AI to help quickly apply consistent, clean styling.

🎨 Prompt Example:

“Here is my JSX for a weather widget. Style it using Tailwind CSS to look clean, minimal, and mobile-responsive like Material Design.”

AI Suggestions Included:

• Proper layout structure using flex, gap, px, py, rounded-lg
• Dark mode and hover states
• Mobile-first breakpoints

While not perfect, this gets me 80% of the way toward a polished UI — great for demos or MVPs.

🚀 5. Integrate AI Into Your IDE

To stay in flow, I use GitHub Copilot in VS Code. It suggests:

• Code completions as I type
• Test case scaffolds
• Common React patterns

🧠 It feels like pairing with a helpful junior dev who always has suggestions.

Bonus tools: Codeium, Tabnine (if you’re not using GitHub Copilot)

🔍 6. Bonus: Refactoring with Claude

When a component grows too large, I use Claude for refactoring. Its long context window makes it perfect for:

• Splitting big components into smaller ones
• Suggesting reusable hooks or context providers
• Cleaning up repeated logic

How to Maximize Your Performance with AI

• Don’t Trust, Verify: AI makes mistakes. Always review and test the code it generates. Think of it as a super-powered junior developer — it’s fast, but it needs supervision.
• Learn from the AI: When an AI model generates a clever solution, take the time to understand it. I’ve learned new techniques and best practices just by analyzing the code it produces.
• Integrate It Into Your IDE: Many code editors now have extensions for AI tools. This allows you to get suggestions and generate code right where you work, which is a massive productivity boost.

The Hard Truth: Evolve or Be Left Behind

Let’s be blunt. AI is not just a shiny new toy; it’s a fundamental shift in how we work. Developers who learn to leverage these tools will be faster, more efficient, and more valuable. Those who resist and insist on doing everything manually will struggle to keep up.

The future of coding is a partnership between human creativity and artificial intelligence. Don’t get left in the past.