Adapt or Get Outcoded: The Engineers Leveraging AI to Dominate Tech

AI-Powered Web Development: A Practical Guide for Engineers

Chelu Martin, a software engineer passionate about AI and automation, recently tackled an exciting challenge—building a website for his wife’s home doctor service, medico a domicilio en Madrid. Instead of taking the traditional development route, he leveraged AI-powered tools and no-code solutions to speed up the process. By combining Lovable AI, Cursor, Supabase, and Vercel, Chelu built and deployed a sleek, optimized website in record time.

For engineers looking to streamline their workflow and experiment with AI-assisted development, Chelu’s journey offers a clear roadmap. But here’s the catch—engineers who don’t adapt to these innovations risk being left behind. In this article, we’ll break down his approach, the tools he used, and key takeaways to help you apply this method to your own projects before it’s too late. You should also check out his post on linkedin where he breaks down the process

The Stack: AI and No-Code in Action

Chelu’s toolset for this project included a mix of AI-powered automation, no-code solutions, and manual refinement:

• Lovable AI – Used to quickly generate much of the initial website structure and content.
• Cursor – An AI-powered code editor, which allowed for fast, efficient refinements.
• Supabase – A backend-as-a-service alternative to Firebase, used to manage data and authentication.
• Vercel – Handled hosting and deployment, ensuring smooth performance and scalability.
• React, Tailwind, and Vite – While new to Chelu, these tools provided flexibility and customization beyond what no-code alone could offer.

This hybrid approach allowed Chelu to benefit from AI-driven efficiency while still maintaining full control over the final product. Meanwhile, engineers who insist on traditional coding methods are wasting time, burning budget, and falling behind.

Step-by-Step Breakdown: How Chelu Built the Website

1. Laying the Foundation with AI-Generated Code

Chelu started by using Lovable AI to generate the core components of the website. This gave him a solid structure to work from without needing to write everything from scratch. He quickly realized that while AI can produce functional code, human intervention was necessary to fine-tune the details and ensure everything worked as intended.

2. Refining the Code with Cursor

While Lovable AI provided the foundation, Cursor allowed Chelu to refine the site efficiently. This AI-assisted development environment helped him debug, restructure components, and optimize the codebase, reducing the time spent on manual coding while keeping full flexibility.

3. Setting Up the Backend with Supabase

For managing user data, Chelu chose Supabase due to its ease of integration and compatibility with modern web applications. Using Supabase, he set up authentication and a simple database structure to support the service’s operational needs.

4. Hosting and Deployment with Vercel

Once the website was functional, Vercel handled deployment, ensuring fast loading speeds and a seamless user experience. Thanks to its streamlined workflow, Chelu was able to push updates effortlessly without dealing with complex infrastructure setup.

5. Fine-Tuning the UI with Tailwind and React

Despite using AI tools to speed up development, Chelu spent time customizing the user interface using React and Tailwind CSS. This final step ensured the site looked polished, professional, and aligned with the service’s branding.

Key Lessons for Engineers Adopting AI-Driven Development

Chelu’s project offers several valuable insights for engineers looking to integrate AI and no-code into their development process:

• AI accelerates, but doesn’t replace engineering skills – While tools like Lovable AI can generate a working base, technical expertise is essential for fine-tuning and debugging.
• Choosing the right stack matters – Combining AI tools with established frameworks (like React and Supabase) ensures flexibility and long-term maintainability.
• Understand AI’s limitations – AI can generate a lot of content, but human oversight is necessary to ensure quality and prevent errors.
• Deployment should be simple – Using platforms like Vercel allows for rapid iteration and scalability with minimal setup.
• No-code can complement, not replace, coding – While non-technical users can get frustrated with no-code tools when they reach their limits, engineers who learn to integrate them will have a significant competitive advantage.

The Future of Engineering: Adapt or Be Left Behind

Chelu’s success with Tu Médico a Domicilio proves that AI and no-code are no longer just experimental concepts—they are practical tools that are already giving forward-thinking engineers a massive competitive edge. If you’re still coding everything from scratch, you’re working harder, not smarter—and you’re losing ground to engineers who leverage AI.

If you want to stay ahead in the industry, consider adopting a similar hybrid approach:

1. Use AI to accelerate initial development – Start with AI-generated code for the foundation.
2. Refine and customize manually – Ensure quality by debugging and optimizing the AI-generated output.
3. Choose a backend-as-a-service like Supabase – Manage data and authentication easily.
4. Deploy effortlessly with Vercel – Focus on development rather than infrastructure setup.
5. Iterate and improve – AI allows for rapid iteration, so refine your product based on user feedback.

At SearchofAI.com, we explore how AI is transforming the way developers build and scale projects. The future is here—are you ready for it? If you’re interested in learning more about AI-powered tools and strategies, check out our platform for the latest insights and recommendations.

Are you ready to experiment with AI-assisted development? Because your competition already is.

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