[lukan]

I lost all my snobism about that years ago and I do just follow the paradigm, "does it work". But for some reasons, even with AI I ain't on another level.

And those reasons are, it all collapses very quickly once the complexity reaches an medium amount.

And if I want to rely on things and debug them - I cannot just have a pile of generated garbage, that works as long as the sun is shining. For isolated tasks it works for me. For anything complex, I am faster on my own.

[Jcampuzano2]

Most replies here make the claim that all AI generated code is "garbage". And I can't help but think most of the people who say that do not actually use it in their day to day with the most recent models and actually give it good instructions/requirements.

No, it is not always perfect. Yes you will have to manually edit some of the code it generates. But yes it can and will generate good code if you know how to use it and use sophisticated tools with good guidance. And there are times where it will even write better more performant code than you could given the time requirements.

[mplanchard]

It writes code well enough in simple contexts, sometimes. But that code is also easy to write, indeed often easier to write than to review. It struggles in more complex contexts and with more complex constraints. Unfortunately, it’s the latter case where I most often have any desire to reach for an aid, and it has failed so consistently and so often there that I have largely stopped trying.

It’s nice when you need to do something simple in an unfamiliar but simple context, though.

It seems though that a lot of the narrative here from its proponents is that we’re just not trying hard enough to get it to solve our problems. It’s like vimmers who won’t shut up about how it’s worth the weeks of cratered productivity in order to reach editing nirvana (I say this as one of them).

Like with any tool, the learning curve has to be justified by the results, but the calculation is further complicated by the fact that the AI tooling landscape changes completely every 3-6 months. Do I want to spend all that time getting good at it now? No. I’ll probably spend more time learning to use it when it’s either easier to get results that actually feel useful or when it stops changing so often.

Until then I’ll keep firing it up every once in a while to have it write some bash or try to get it to write a unit test.

[Glyptodon]

I find it very hit or miss, but I definitely use it. I just don't think it's making vastly more productive yet, maybe 30%. I do think it will get good enough that my job may turn into 80% writing tickets or refining tickets for AI "engineers" and 20% fixing/debugging issues with AI output. But not there yet, and still don't think it will be trustworthy enough to let loose without someone technical in the loop doing that review/fixing. But that might be enough to make one generalist CRUD engineer into the equivalent of a team of 4 or 5 in a couple years.

I kind of see it replacing outsourcing, not mid level + engineers so far. But expect to lead to making mid level + about as productive as a small team.

[lyu07282]

I think the root of the argument is that the AI critics are worried because they have the assumption that 1) you aren't experienced enough to know what "good code" looks like, and/or 2) you only care if it "works" and don't understand all the implications bad code will have downstream, again because of inexperience.

[lukan]

If the code is a isolated module or function, all is well.

Otherwise often not. But I am not worried. Give me a AI tool that can work with my whole codebase reliable and I gladly use it.