> and before you discount it as too trivial, somehow none of the other ones did what I wanted

No offense, it's really great that you are able to make apps that do exactly what you want, but your examples are not very good to show that "software projects that somehow are 100% human developed will not be competitive with AI assisted or written projects" (as someone else suggested above). Complex real world software is different from pomodoro timers and TODO lists.

> Complex real world software is different from pomodoro timers and TODO lists.

Simplistic Pomodoro timer with no features, sure, but a full blown modern Todo app that syncs to configurable backend(s), has a website, mobile apps, an electron app, CLI/TUI, web hooks, other integrations? Add a login system and allow users to assign todos to each other, and have todos depend on other todos and visualizations and it starts looking like JIRA, which is totally complex real world software.

The weakness of LLMs is that they can't do anything that's not in their training data. But they've got so much training data that say you had a box of Lego bricks but could only use those bricks to build models. If you had a brick copier, and one copy of every single brick type on the Internet, the fact that you couldn't invent new pieces from scratch would be a limitation, but given the number of bricks on all the Internet, that covers a lot of area. Most (but not all) software is some flavor of CRUD app, and if LLMs could only write every CRUD app ever that would still be tremendous value.

Cut it out with patronising, I work with complex software, which is why I specifically mentioned the only example I published was simple.

> but your examples are not very good to show that "software projects that somehow are 100% human developed will not be competitive with AI assisted or written projects"

Here's the thing though - it's already the case, because I wouldn't create those tools but hand otherwise. I just don't have the time, and they're too personal/edge-case to pay anyone to make them. So the comparison in this case is between 100% human developed non-existent software and AI generated project which exists. The latter wins in every category by default.

My apologies, I didn't want to sound patronizing and wasn't making assumptions about your work and experience based on your examples, I am happy that generative AI allows you to make such apps. However, they are very similar to the demos that are always presented as showcases.

I don't think they're being patronizing, it's that "simple personal app that was barely worth making" is nice to have but not at all what they want evidence of.

Whether it was worth making is for me to judge since it is a personal app. It improves my life and work, so yes, it was very much worth it.

You said you wouldn't have made it if it took longer, isn't that a barely?

But either way it's not an example of what they wanted.

> The time to make them generic enough to share would be much longer than creating my specific version in the first place

Welcome to the reality of software development. "Works on my machine" is often not good enough to make the cut.

It doesn't matter that my thing doesn't generalise if someone can build their own customised solution quickly. But also, if I wanted to sell it or distribute it, I'd ensure it was more generic from the beginning.

You need to put your money where your mouth is.

If you comment about AI generated code in a thread about qemu (mission-critical project that many industries rely upon), a pomodoro app is not going to do the trick.

And no, it doesn't "show that is possible". qemu is not only more complex, it's a whole different problem space.