Usually the "10x" improvements come from greenfield projects or at least smaller codebases. Productivity improvements on mature complex codebases are much more modest, more like 1.2x.

If you really in good faith want to understand where people are coming from when they talk about huge productivity gains, then I would recommend installing Claude Code (specifically that tool) and asking it to build some kind of small project from scratch. (The one I tried was a small app to poll a public flight API for planes near my house and plot the positions, along with other metadata. I didn't give it the api schema at all. It was still able to make it work.) This will show you, at least, what these tools are capable of -- and not just on toy apps, but also at small startups doing a lot of greenfield work very quickly.

Most of us aren't doing that kind of work, we work on large mature codebases. AI is much less effective there because it doesn't have all the context we have about the codebase and product. Sometimes it's useful, sometimes not. But to start making that tradeoff I do think it's worth first setting aside skepticism and seeing it at its best, and giving yourself that "wow" moment.

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 was able to realize huge productivity gains working on a 20 years old codebase with 2+ million loc, as I mentioned in the sister post. So I disagree that big productivity gains are only on greenfield projects. Realizing productivity gains on mature code based requires more skill and upfront setup. You need to put some work in your claude.md and give Claude tools for accessing necessary data, logs, build process. It should be able to test your code autonomously as much as possible. In my experience, people who say they are not able to realize productivity gains don't put enough effort to understand these new tools and setup them properly for their project.