OR it has to be a situation catastrophic enough. I don't think this one is, but it's hard to be optimistic for the future

As far as perennity is concerned it seems strictly better.

Because it feels like people argue as if they were talking about the former, but if probed it turns out they admit it's the latter.

There will be still people making car advertisements, but they will be using ai tools and will get asked to produce X times faster. Effectively, some of them will get replaced, or rather have been replaced.

The answer is still the same as well, people learn ocaml either because they enjoy it, or because learning a functional language makes them a better programmer overall and teaches your brain to approach a problem in a different way.

Before AI just having a good README and superficially looking good code (we're not going to do a deep review of it) was a gauge of quality that at the very least the person that wrote it knows what it's doing.

How do you do it now? Maybe the AI was expertly guided, but maybe it was vibe-coded by someone who hasn't even heard of basic security principles and your whole data is sent in plain-text somewhere. It doesn't have to be nefarious, it could be a debug feature that was never removed, or maybe the user never asked the llm to "make it prod safe". And there's no way to know unless you read the whole thing, because superficially the README and the code will look as good as any other llm project.

That's problem number one, before you could quickly see if it's made by someone who knows what it's doing, and thus that you can trust. With vibe-coded software not so much.

The second issue is not inherent to vibe-coded software but it's caused by it: it's a sea of garbage. It's very possible that the absolute amount of good software has increased, but it's become harder to find it.

As of now there's no guarantee of... anything, really.

Obviously if you decide to send an email to the US you're choosing to send your data there, that's a strawman.

The "run a task periodically" isn't the difficult part, it's processing the data that is.

And to be honest I don't think llms will empower that many people, the vast majority don't want to put the effort required (and it's definitely more effort than writing a one-shot prompt)

That means at least from their POV what's already available is not enough or not good enough, and if they're correct then the companies making the models can "artificially" inflate a language's representation.

But who knows? Maybe it would lower the barrier instead. If switching to fossil is just one agent.md instruction away and it brings useful features with minimal effort, it might be an easier sell than without them.

After all, the new generation of programmers won't bother learning git anyway.

It's on me for procrastinating playing the game for so long, it was bound to happen.

In any case it's not practical to carry your dotfiles everywhere you go. Changes are also a hassle to propagate

Not terrible, but I'll just point my own llm to it instead of reading it myself like I would for an actual great documentation