Why HTML Generation Wasn't Enough: The Evolution of SiteGen AI

After building the first version of SiteGen AI, I was excited to see websites being generated from simple prompts.

The application could generate HTML, CSS, and JavaScript based on user input. It was a great milestone because it proved that the core idea worked.

However, after testing more prompts and creating different types of websites, I started noticing a pattern.

The generated websites looked functional, but they weren't complete applications.

The Limitation

If a user asked for a portfolio website, SiteGen AI could generate a portfolio page.

If someone requested a restaurant website, it could generate a landing page.

But what happened when someone asked for something larger?

For example:

Build a Hospital Management System.

The application still generated a single webpage.

A real hospital management system requires much more than a homepage.

It needs authentication, dashboards, APIs, databases, user roles, appointment management, and many other components.

That's when I realized my application wasn't generating software.

It was only generating webpages.

The Difference Between a Website and a Software Project

A modern software project usually consists of multiple parts.

• Frontend
• Backend
• Database
• Authentication
• REST APIs
• Deployment configuration
• Documentation

Generating only HTML, CSS, and JavaScript solves only one part of the problem.

The remaining architecture still has to be built manually.

Rethinking the Architecture

Instead of improving the HTML generator, I started thinking differently.

The first question became:

"What does the user actually want to build?"

Instead of immediately generating code, the application should first understand the project requirements.

For example, if a user asks for an e-commerce application, the system should identify that it requires:

• Product management
• Shopping cart
• Authentication
• Payment integration
• Database
• Admin dashboard
• User dashboard

Only after understanding these requirements should the code generation begin.

This approach completely changes how the application works.

A New Direction

This realization marked the beginning of SiteGen AI v2.

The goal is no longer to generate individual webpages.

The goal is to generate complete software projects.

Instead of returning three files—

• index.html
• style.css
• script.js

—I want SiteGen AI to generate an organized project structure with frontend, backend, database, documentation, and deployment configuration.

This is a much larger challenge, but it also makes the project far more useful.

Lessons Learned

One of the biggest lessons from building the first version is that writing code is only one part of software development.

Understanding requirements, planning architecture, and generating maintainable project structures are equally important.

The quality of an AI-generated application depends on the quality of its planning before any code is written.

What's Next

In the next article, I'll explain why I migrated from the Gemini API to OpenRouter, what challenges I faced with API quotas, and how abstracting the AI provider made the project more flexible for future development.

Thank you for reading.