As an AI prompt engineer and ChatGPT expert, I recently embarked on an exciting journey to create my professional portfolio using the latest AI technology. This project not only showcased the incredible capabilities of AI-assisted development but also highlighted the crucial role of human expertise in guiding and refining AI outputs. In this comprehensive guide, I'll take you through my process, share key insights, and explore the cutting-edge developments in AI-assisted software development as of 2025.
Why ChatGPT for Portfolio Creation?
Before diving into the specifics, it's important to understand the rationale behind using ChatGPT for this project:
- Pushing AI Boundaries: As a prompt engineer, I wanted to test the limits of what's possible with AI-assisted development.
- Real-World Application: Creating a portfolio is a common task for developers, making it an excellent test case for AI capabilities.
- Skill Synergy: The project offered a unique opportunity to blend my technical skills with advanced AI assistance.
- Staying Current: With ChatGPT-5 released in early 2025, I wanted to explore its enhanced capabilities in code generation and project planning.
The Development Process: A Step-by-Step Journey
1. Setting Up the Development Environment
My first step was to establish a robust foundation for the project. I prompted ChatGPT-5 with:
"Create a modern React application using Vite, TypeScript, and the latest best practices for 2025."
ChatGPT-5 responded with an up-to-date guide, including:
- A check for the latest Node.js version (v18.x as of 2025)
- Commands to create a React application with Vite and TypeScript:
npm create vite@latest my-portfolio -- --template react-ts - Instructions for installing dependencies and running the development server
- Suggestions for additional tools like ESLint and Prettier with the latest configurations
What impressed me most was ChatGPT-5's ability to provide information on the newest features in React 19 and TypeScript 5.2, which were released in late 2024. This demonstrated the AI's capacity to stay current with rapidly evolving technologies.
2. Structuring the Portfolio
Next, I asked ChatGPT to suggest a modern, scalable structure for a portfolio site. The AI provided an advanced project structure:
src/
├── components/
│ ├── ui/ # Reusable UI components
│ ├── layout/ # Layout components (Header, Footer, etc.)
│ └── sections/ # Page-specific sections
├── pages/ # Page components
├── hooks/ # Custom React hooks
├── styles/ # Global styles and theme
├── utils/ # Utility functions and constants
├── services/ # API services and data fetching
├── context/ # React context providers
├── types/ # TypeScript type definitions
└── assets/ # Static assets
This structure not only aligned with React best practices but also incorporated newer concepts like the separation of UI components and the use of custom hooks for better code organization.
3. Component Development
ChatGPT generated initial code for the Header and Footer components using the latest React and TypeScript syntax:
// src/components/layout/Header.tsx
import { useState } from 'react';
import { Link } from 'react-router-dom';
export default function Header() {
const [isMenuOpen, setIsMenuOpen] = useState(false);
return (
<header>
<nav>
<Link to="/">Home</Link>
<Link to="/about">About</Link>
<Link to="/projects">Projects</Link>
<Link to="/contact">Contact</Link>
</nav>
<button onClick={() => setIsMenuOpen(!isMenuOpen)}>
Menu
</button>
{isMenuOpen && (
<div className="mobile-menu">
{/* Mobile menu items */}
</div>
)}
</header>
);
}
// src/components/layout/Footer.tsx
export default function Footer() {
return (
<footer>
<p>© 2025 My Portfolio. All rights reserved.</p>
<div>
<a href="https://github.com/yourusername">GitHub</a>
<a href="https://linkedin.com/in/yourusername">LinkedIn</a>
</div>
</footer>
);
}
I was impressed by ChatGPT-5's use of modern React patterns, such as:
- Functional components with hooks
- TypeScript for type safety
- React Router v6 for navigation
- Consideration for mobile responsiveness
Skills Section
For the skills section, I prompted ChatGPT to create a dynamic, visually appealing component. The AI suggested using the Intersection Observer API for scroll-based animations and generated the following code:
// src/components/sections/SkillsSection.tsx
import { useEffect, useRef, useState } from 'react';
import { SkillCard } from '../ui/SkillCard';
import { skills } from '../../data/skills';
export default function SkillsSection() {
const [visibleSkills, setVisibleSkills] = useState<string[]>([]);
const sectionRef = useRef<HTMLDivElement>(null);
useEffect(() => {
const observer = new IntersectionObserver(
(entries) => {
entries.forEach((entry) => {
if (entry.isIntersecting) {
setVisibleSkills((prev) => [...prev, entry.target.id]);
}
});
},
{ threshold: 0.5 }
);
const skillElements = sectionRef.current?.querySelectorAll('.skill-card');
skillElements?.forEach((el) => observer.observe(el));
return () => observer.disconnect();
}, []);
return (
<section ref={sectionRef}>
<h2>My Skills</h2>
<div className="skills-grid">
{skills.map((skill) => (
<SkillCard
key={skill.id}
{...skill}
isVisible={visibleSkills.includes(skill.id)}
/>
))}
</div>
</section>
);
}
This component demonstrated ChatGPT-5's understanding of:
- Advanced React hooks (useEffect, useRef)
- Modern browser APIs (Intersection Observer)
- Performance considerations for animations
- TypeScript for improved type safety
I further enhanced this component by implementing CSS modules for scoped styling and adding keyboard navigation for accessibility.
4. State Management and Data Fetching
Given the evolving landscape of state management in React, I asked ChatGPT-5 for recommendations on managing global state and fetching data. The AI suggested using a combination of React Query (now called TanStack Query) for data fetching and Zustand for global state management.
Here's an example of how ChatGPT-5 suggested implementing a custom hook for fetching projects:
// src/hooks/useProjects.ts
import { useQuery } from '@tanstack/react-query';
import { fetchProjects } from '../services/api';
export function useProjects() {
return useQuery({
queryKey: ['projects'],
queryFn: fetchProjects,
staleTime: 5 * 60 * 1000, // 5 minutes
});
}
And for global state management:
// src/store/useThemeStore.ts
import { create } from 'zustand';
type Theme = 'light' | 'dark';
interface ThemeState {
theme: Theme;
toggleTheme: () => void;
}
export const useThemeStore = create<ThemeState>((set) => ({
theme: 'light',
toggleTheme: () => set((state) => ({ theme: state.theme === 'light' ? 'dark' : 'light' })),
}));
These suggestions aligned perfectly with the latest best practices in React development, emphasizing:
- Separation of concerns
- Efficient data fetching and caching
- Lightweight and flexible state management
5. Styling and Effects
To enhance the visual appeal of the portfolio, I asked ChatGPT for modern styling solutions. The AI recommended using CSS-in-JS with the latest version of styled-components, which offers better TypeScript integration and improved performance.
Here's an example of a styled component generated by ChatGPT-5:
// src/components/ui/Button.tsx
import styled from 'styled-components';
const StyledButton = styled.button<{ $primary?: boolean }>`
background: ${(props) => (props.$primary ? props.theme.primaryColor : 'white')};
color: ${(props) => (props.$primary ? 'white' : props.theme.primaryColor)};
font-size: 1em;
margin: 1em;
padding: 0.25em 1em;
border: 2px solid ${(props) => props.theme.primaryColor};
border-radius: 3px;
cursor: pointer;
transition: all 0.3s ease;
&:hover {
background: ${(props) => (props.$primary ? 'white' : props.theme.primaryColor)};
color: ${(props) => (props.$primary ? props.theme.primaryColor : 'white')};
}
`;
export default function Button({ primary, children, ...props }) {
return <StyledButton $primary={primary} {...props}>{children}</StyledButton>;
}
This component showcases:
- TypeScript integration with styled-components
- Theme support for consistent styling
- Accessibility considerations with proper contrast
- Performance optimizations with the use of the
$prefix for transient props
Key Learnings and Insights
Throughout this process, several important lessons emerged:
AI as a Collaborative Partner: ChatGPT-5 proved to be an invaluable collaborator, offering suggestions, generating code, and providing up-to-date information on best practices.
The Evolving Role of the Developer: While AI can generate substantial portions of code, the developer's role has shifted towards:
- Crafting precise prompts to guide AI output
- Critically evaluating and refining AI-generated code
- Making high-level architectural decisions
- Ensuring accessibility, performance, and user experience
Importance of Staying Current: The rapid pace of technological change in web development necessitates continuous learning, even (or especially) when working with AI.
AI's Impact on Development Workflow: Using ChatGPT-5 significantly accelerated certain aspects of development, such as:
- Initial project setup and boilerplate code generation
- Problem-solving and debugging (by providing detailed error descriptions)
- Documentation and code commenting
Ethical Considerations: As AI becomes more integrated into the development process, it's crucial to consider:
- Proper attribution of AI-generated code
- Ensuring the uniqueness and originality of the final product
- Maintaining transparency with clients about AI usage in projects
The Future of AI-Assisted Development
As we look towards the future, several trends are emerging in AI-assisted development:
Increased Specialization: Future AI models may be fine-tuned for specific programming languages or frameworks, offering more targeted assistance.
Real-time Collaboration: We may see AI assistants integrated directly into IDEs, offering real-time suggestions and code completion.
Automated Testing and Optimization: AI could play a larger role in generating test cases, identifying potential performance bottlenecks, and suggesting optimizations.
Natural Language Programming: As AI language models improve, we may see a shift towards more natural language interfaces for programming, making coding more accessible to non-technical users.
AI-Driven Architecture Decisions: Future AI models might be capable of suggesting entire application architectures based on project requirements.
Conclusion: Embracing AI in Software Development
Creating my portfolio with ChatGPT-5's assistance was an enlightening experience that showcased both the immense potential and current limitations of AI in software development. As an AI prompt engineer, I found that the key to success lies in:
- Leveraging AI for rapid prototyping, idea generation, and problem-solving
- Applying human expertise to refine, optimize, and critically evaluate AI outputs
- Staying updated with industry best practices and emerging technologies
- Developing strong prompt engineering skills to effectively guide AI assistance
This project demonstrates that while AI tools like ChatGPT are incredibly powerful, they are most effective when paired with skilled developers who can guide their use and interpret their outputs. As we move forward, the ability to effectively collaborate with AI will become an increasingly valuable skill in the tech industry.
By sharing this experience, I hope to inspire other developers to explore the possibilities of AI-assisted development while emphasizing the ongoing importance of human creativity, expertise, and critical thinking in the software development process. As AI continues to evolve, so too will the role of developers, leading to exciting new possibilities in the world of software creation.
