QIQI

I've been thinking about how the definition of MVP is changing. In the past, building an MVP usually meant spending weeks or months creating the smallest version of a product that could test an idea. Now, with AI tools, someone can build a working prototype in days or even hours. But I wonder if the bottleneck has moved: Is the MVP still the product itself? Or is it now the fastest way to test whether users actually care? How much should founders build before talking to customers? I've noticed that it's easier than ever to create something functional, but much harder to know whether you're building the right thing. For founders who have launched MVPs:

What was the biggest lesson you learned from your first version?

I don't know if this works for everyone or only for me. First of all, I think when AI coding tools first became popular, the biggest excitement was that anyone could build software without years of programming experience. But after experimenting with these tools, I think the hardest part has shifted. Writing prompts is becoming easier. The real challenges are:

• Knowing what to build

• Turning an idea into a product users actually need

• Debugging unexpected problems

• Making the app reliable enough for real users

AI can help you create a prototype quickly, but building a real product still requires product thinking, iteration, and understanding users. I m curious about people who have used AI coding tools to launch something:

What was the biggest bottleneck after your first version was built?

A few years ago, the biggest challenge for building a software product was usually technical skills.

Today, with AI coding tools, someone with limited coding experience can create a functional MVP in days or even hours.

But I m starting to wonder if the bottleneck has simply moved somewhere else.

Building is becoming easier, but: