GPT-4o Coding Examples: Real Use Cases Every Developer Should Know

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GPT-4o Coding Examples

🧠 Introduction: The Rise of GPT-4o in the Developer World

Since OpenAI released GPT-4o, it has dramatically transformed how developers build, test, and deploy software. While earlier versions like GPT-3.5 and GPT-4 were impressive, GPT-4o (“o” for “omni”) brings multi-modal power, faster response time, and better context understanding — making it a dream tool for developers in 2025.

From writing complex algorithms to designing APIs and debugging real-world codebases, GPT-4o is not just an assistant — it’s your co-developer. This article walks you through real coding examples using GPT-4o that you can try in your projects, broken down by category.

🚀 What Makes GPT-4o Special for Developers?

Here’s why GPT-4o is more powerful than its predecessors:

  • ✅ Faster code generation with better accuracy

  • ✅ Deeper reasoning capabilities for understanding complex logic

  • ✅ Multi-modal input: Handle text, code, images, and even audio

  • ✅ Better memory handling: Long code context support

  • ✅ Improved debugging, refactoring, and documentation

Two women working together on educational materials in a classroom setting.

🧪 Real Coding Examples with GPT-4o (Categorized)

Let’s now explore real coding examples across different use cases, complete with prompts and outputs you can try today.

💻 1. Web Development with GPT-4o

🟢 Example 1: Responsive Navbar in HTML + TailwindCSS

Prompt:

“Create a responsive navbar using TailwindCSS with a hamburger menu for mobile.”

GPT-4o Output:

html
<nav class="bg-white shadow-md p-4 flex justify-between items-center">
<h1 class="text-xl font-bold">MySite</h1>
<button class="md:hidden">
<svg class="w-6 h-6" fill="none" stroke="currentColor">...</svg>
</button>
<ul class="hidden md:flex space-x-4">
<li><a href="#" class="text-gray-700">Home</a></li>
<li><a href="#">About</a></li>
<li><a href="#">Contact</a></li>
</ul>
</nav>

➡️ Benefit: GPT-4o provides production-ready, responsive UI components with accessibility tags.

🐍 2. Python Scripting & Automation

🟢 Example 2: CSV to JSON Converter

Prompt:

“Write a Python script to convert a CSV file to JSON.”

GPT-4o Output:

python
import csv
import jsonwith open(‘data.csv’) as csv_file:
csv_reader = csv.DictReader(csv_file)
data = list(csv_reader)

with open(‘data.json’, ‘w’) as json_file:
json.dump(data, json_file, indent=4)

✅ Plug-and-play code with explanations when prompted:

“Explain line by line what this script does.”

🧰 3. Debugging Real Code with GPT-4o

🟢 Example 3: Fixing React “undefined” Error

Prompt:

“I’m getting ‘Cannot read property map of undefined’ in my React component. Fix it.”

GPT-4o Output:

jsx
{data && data.length > 0 ? (
data.map(item => <div key={item.id}>{item.name}</div>)
) : (
<p>No data found</p>
)}

➕ It will also suggest:

  • Add PropTypes or TypeScript for safety

  • Debug tips (e.g., check API call response structure)

🛠️ 4. Backend Development with GPT-4o

🟢 Example 4: Node.js JWT Authentication

Prompt:

“Create an Express.js route with JWT-based login authentication.”

GPT-4o Output:

js
app.post('/login', async (req, res) => {
const { username, password } = req.body;
const user = await findUser(username, password);
if (!user) return res.status(401).send('Unauthorized');const token = jwt.sign({ id: user.id }, ‘secretKey’, { expiresIn: ‘1h’ });
res.json({ token });
});

➡️ GPT-4o also advises adding middlewares like express-validator and helmet for security.

🧪 5. Unit Testing & TDD

🟢 Example 5: Jest Test for a Calculator

Prompt:

“Write Jest unit tests for a calculator function (add, subtract, multiply, divide).”

GPT-4o Output:

js
test('adds 2 + 2 to equal 4', () => {
expect(add(2, 2)).toBe(4);
});test(‘divides 10 by 2 to equal 5’, () => {
expect(divide(10, 2)).toBe(5);
});

➕ Bonus: GPT-4o suggests adding edge case tests like dividing by 0.

🖼️ 6. Multi-Modal Coding (With Image Input)

🟢 Example 6: Explain Code from Screenshot

Prompt:

Upload a screenshot of code

Ask: “What does this code do? Are there any issues?”

GPT-4o Output:
GPT-4o reads the code from the image and provides a detailed explanation along with suggested improvements.

This is a breakthrough use-case — GPT-4o can now understand visual code input, a feature developers are loving in 2025.

🔍 7. Refactoring & Optimization

🟢 Example 7: Optimize SQL Query

Prompt:

“Optimize this SQL query for better performance on large tables.”

GPT-4o Output:

sql
SELECT name FROM employees WHERE department_id = 2 AND status = 'active'
ORDER BY created_at DESC LIMIT 100;

Plus, it explains why:

  • Using indexes

  • Removing subqueries

  • Limiting row scans

🌐 8. API Development & Integration

🟢 Example 8: FastAPI with Swagger Docs

Prompt:

“Create a FastAPI app with Swagger UI and one GET endpoint.”

GPT-4o Output:

python

from fastapi import FastAPI

app = FastAPI()

@app.get(“/hello”)
def read_root():
return {“message”: “Hello GPT-4o”}

You’ll get Swagger docs by default at /docs.

🎨 9. Frontend + AI Combo

🟢 Example 9: AI-Powered Chat UI

Prompt:

“Build a simple chat interface using HTML/CSS/JS that connects to OpenAI API.”

GPT-4o Output:
Generates the form, fetch request with API key, and error handling — all with responsiveness.

This is great for building custom ChatGPT tools or widgets.

📊 10. Data Science & ML with GPT-4o

🟢 Example 10: Linear Regression with scikit-learn

Prompt:

“Create a Python script that performs linear regression using scikit-learn.”

GPT-4o Output:

python
from sklearn.linear_model import LinearRegression
import numpy as npX = np.array([[1], [2], [3]])
y = np.array([2, 4, 6])

model = LinearRegression().fit(X, y)
print(model.coef_, model.intercept_)

➕ Ask: “Visualize this regression with matplotlib”
And GPT-4o will generate the graph code too.

🔑 How to Prompt GPT-4o for Best Results

  • 🎯 Be specific: Include versions, frameworks, and expected output

  • 📂 Add context: Use “Here is my code + here’s what I expect”

  • ⛓️ Chain prompts: Use follow-ups like “Now convert to TypeScript” or “Now test this”

  • 💬 Ask for alternatives: “Give me 3 ways to solve this”

🌟 Real-World Use Cases from Devs in 2025

  1. Startup Teams – Building MVPs in record time

  2. Freelancers – Delivering quick, accurate solutions for clients

  3. Enterprise Developers – Rapidly debugging legacy systems

  4. Educators – Creating code examples and lesson plans

  5. AI App Builders – Integrating GPT-4o into SaaS platforms

❌ Limitations to Keep in Mind

  • May hallucinate or guess if input is unclear

  • Doesn’t always know about proprietary APIs or closed libraries

  • Requires manual validation for production code

  • Output varies with vague or low-context prompts

Two male developers at desks programming in a modern office workspace with large monitors.

📚Additional GPT-4o Code Examples You Can Try

  • “Build a drag-and-drop task manager in React.”

  • “Create a script to backup a MySQL DB to Google Drive.”

  • “Write a bash script to check server uptime.”

  • “Design a schema for a social media app with likes and comments.”

  • “Create an HTML email template for newsletters.”

❓ FAQs

Q1. Can GPT-4o write production-ready code?
Yes, but it should be reviewed and tested manually.

Q2. Does GPT-4o support all programming languages?
It supports almost all major languages: Python, JavaScript, Go, C++, Java, Rust, etc.

Q3. Can GPT-4o read code from images or screenshots?
Yes! That’s one of GPT-4o’s most unique features.

Q4. Is GPT-4o better than Copilot?
For understanding, explaining, and multi-step tasks, yes. Copilot is better for in-line suggestions inside IDEs.

🎯 Final Thoughts: GPT-4o Is the Future of Developer Productivity

Whether you’re building apps, analyzing data, deploying cloud infrastructure, or debugging messy legacy code — GPT-4o is now an essential part of a developer’s toolkit.

The difference lies in how well you use it. With the right prompts, context, and follow-ups, GPT-4o can help you deliver code faster, smarter, and with fewer bugs.

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