🚀 Vibe coding can generate thousands of lines of code. It still can't generate product-market fit.

Over the past few months, I've been experimenting with AI-assisted development, and it's completely changed how quickly I can go from idea to MVP.

But it's also made me question something.

We've become incredibly good at generating code.

Have we become equally good at deciding what to build?

I keep coming back to this simple thought:

def build_startup(idea):
    validate_market(idea)
    understand_customers()
    analyze_competitors()

    if not real_problem():
        return "Don't build yet."

    return vibe_code_mvp()

AI makes the last line incredibly fast.

The first four lines still seem to be where most startups succeed or fail.

I'm curious how everyone else is approaching this.

• Do you validate ideas before opening Cursor, Claude Code, or GitHub Copilot?

• Has vibe coding changed how you think about product-market fit?

• What's the biggest lesson you've learned after shipping an AI-built MVP?

• Have you ever built something quickly with AI that ultimately solved the wrong problem?

One thing I've noticed is that the bottleneck seems to be shifting.

It used to be building software.

Now it feels like the bottleneck is making better product decisions.

Is anyone else seeing the same pattern, or has your experience been different?