Building became the easiest part. That surprised me.

When we started building Autocoder, I thought the hardest part would be writing software. Turns out, AI solved a big part of that. Today, I can go from an idea to a working prototype in hours instead of weeks. That's incredible. But something unexpected happened. The faster we built, the more often we built the wrong thing. We spent time polishing features that nobody asked for. We improved workflows that users didn't actually care about. We optimized before we validated. Eventually, we changed the way we worked.

Instead of asking:

"Can we build this?"

we started asking:

"What are we trying to learn?"

That small mindset shift changed everything. Now every prototype is just an experiment. If nobody uses it, we delete it. If users love it, then we invest in making it better. Ironically, AI didn't make building the competitive advantage. It made learning faster. That's one of the reasons we built Autocoder—to remove the friction between an idea and something real that people can actually react to. Once building becomes cheap, your biggest advantage isn't coding anymore—it's knowing what deserves to be built.

I'm curious: Has AI changed the way you build products, or only the speed at which you build them?

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