So, I'm doing that right now. You do get wow moments, but then you rapidly hit the WTF are you doing moments.

One of the first three projects I tried was a spin on a to-do app. The buttons didn't even work when clicked.

Yes, I keep it iterating, give it a puppeteer MCP, etc.

I think you're just misunderstanding how hard it is to make a greenfield project when you have a super-charged stack overflow that AI is.

Greenfield projects aren't hard, what's hard is starting them.

What AI has helped me immensely with is blank page syndrome. I get it to spit out some boilerplate for a SINGLE page, then boom, I have a new greenfield project 95% my own code in a couple of days.

That's the mistake I think you 10x ers are making.

And you're all giddy and excited and are putting in a ton of work without realising you're the one doing the work, not the AI.

And you'll eventually burn out on that.

And those of us who are a bit more skeptical are realising we could have done it on our own, faster, we just wouldn't normally have bothered. I'd have gone done some gardening with that time instead.

I'm not a 10x-er. My job is working on a mature codebase. The results of AI in that situation are mixed, 1.2x if you're lucky.

My recommendation was that it's useful to try the tools on greenfield projects, since they you can see them at their best.

The productivity improvements of AI for greenfield projects are real. It's not all bullshit. It is a huge boost if you're at a small startup trying to find product market fit. If you don't believe that and think it would be faster to do it all manually I don't know what to tell you - go talk to some startup founders, maybe?