Experimenting with AI Tools for Building Websites

I’ve been fascinated by AI-assisted development and the accelerating shift in how software gets built. Tools like Cursor, ChatGPT, and Claude have become staples in my daily developer toolkit. But beyond these, I’ve been exploring a new wave of AI tools designed specifically for building websites and applications - tools that attempt to take entire chunks of the development process off your plate.

Here are two I’ve tested recently that are worth a closer look.

v0 by Vercel

v0 is an AI UI generator by Vercel that turns plain text prompts into working interfaces. It works well alongside frameworks like Next.js, TailwindCSS, and shadcn/ui, which I selected as the tech stack for my project.

I’d been hearing about v0’s capabilities in creating user interfaces, so I was glad for a chance to take it for a spin. I used it to design and create the UI for Pooped Puppies, a puppy training school website.

To set the project up for success, I wrote a thorough project document. One thing I’m finding when working with AI agents: the more detailed your instructions, the better the outcome - much like managing a junior developer or onboarding someone to a large codebase.

Based on my specs, v0 generated the UI components and page structures. The design came out clean and polished, and when I asked for changes, it was quick and easy to refine them inside the v0 environment. Once the UI was dialed in, I exported the project and downloaded the codebase to continue development in Cursor.

I was impressed with the code quality. The structure followed best practices, and the components were clean and well-formed. It gave me a solid starting point to add interactivity and backend integration without needing to reorganize or refactor. Overall, I’d rate v0 very highly for UI prototyping and plan to continue using it as a go-to tool when kicking off new web projects.

Replit

Replit is an all-in-one browser-based development environment that has embraced agentic coding with its own built-in AI tools. It’s designed to help anyone - from beginners to pros - spin up and deploy projects with minimal setup.

Replit was one of the first platforms to embrace "AI coding agents," and I had a chance to use it in a real-world scenario when a friend sent me the first of what I expect will become a common message:

“I created this app using AI, but now it’s broken and the agent can’t seem to fix it. Can you help me make it work?”

I wasn’t surprised. It wasn't too hard to predict that the rise of “vibe coding” would create a new kind of technical debt. 😁

I logged in, explored the app, and found the Replit IDE and chat interface to be pretty intuitive. Within a couple of hours, I had the app running again. But it wasn’t as simple as prompting my way through it - the AI agent had hit some blind spots and couldn't see the problem. It took some good old-fashioned human debugging to get things back on track.

Once the core issue was resolved, the AI agent was able to jump back in and assist with writing code and updating the app effectively.

What struck me most was that my friend, a designer by trade, had managed to build a pretty complex app that integrated APIs and live data - all without traditional coding knowledge. That’s powerful, and I’m excited to see this technology mature.

Conclusion

These tools are impressive for rapidly prototyping UI, spinning up MVPs, or automating repetitive dev tasks. Will they replace developers? Not even close. But they are going to replace much of the low-level grunt work - and developers who embrace them will move faster than those who don’t.

That said, these tools are not yet producing production-ready apps without oversight. The generated code can have security issues, scalability limitations, and hidden bugs. The key is using them as accelerators, not substitutes.

TL;DR

Strengths:

• Rapid prototyping and MVP creation
• Making app development accessible to non-coders
• Speeding up experienced developers
• Genuinely fun - prompting up a working app is still a thrill

Weaknesses:

• Can stumble hard on complex projects
• Easy for beginners to get overconfident
• Generated code can have security and reliability gaps
• Unreviewed code can become technical debt fast