If AI is that good, can someone code a good XML library with AI? The spec is available.
If AI is that good, there should be an explosion of Open Source projects of good quality.
Neither of those is happening.
replies(11):
If AI is that good, there should be an explosion of Open Source projects of good quality.
Neither of those is happening.
I don't want to speak for the person you replied to, but I think that their main point is... are they?
I see lots of articles about huge increases in productivity, but I think it's fair to argue that we've yet to see the huge increases in useful products that would surely (we hope) result from that if it were true.
People should realize that denying that AI can boost productivity in coding makes it look like they don't know how to use it, or believe in some conspiracy that no one is actually benefitting and it's all market hype from tech bros.
One thing I've noticed about the super-AI enthusiasts on HN is that not a single one ever have a single comment linking to a repo of work they've made with it.
I check. I actually always do because I'm really keen to learn how to use these magical super-AI workflows. I've watched streams, replicated clause MD files, tried all the context tricks.
I'm not even saying AI doesn't help, it's great for getting me over the blank page writer's block. It's just not great at much else.
So I've just checked your comments and not only do you not have any examples of your super-duper AI skills, but it looks like you've been in the industry less than a year, graduating from a PhD last year?
You also admit it took you a week trying to debug a problem before an AI fixed it for you. Because you'd missed some parentheses in an algo.
I'm not trying to shame you, but that does signal your inexperience. If you'd have made the code well and easy to test, you should have spotted your bad algo quickly.
So is it that we're all bad at using AI? Or is it that AI benefits inexperienced programmers more?
The bad algo was a scaling problem for one equation. That particular equation wasn't some y = mx + b thing, it was the result of a discontinuous galerkin finite element scheme that I wrote from scratch. The actual equation was one that I found after about 2 pages of hand written derivations with high level math. Not really a coding issue, just an algebra issue after really intense manipulations of partial differential equations.
The fact that AI found that problem, a problem that could only be found by someone able to do complex manipulations of PDEs is incredible to me. Perhaps I didn't tell the story well in the past comment, but it isn't like I didn't know python syntax and AI held my hand.
I don't post repos because I keep my hacker news life separate from my personal life, and my repos are tied to my name.
Most major software companies are demanding that their employees use AI, so you should be able to look at any open repo from Google, Microsoft, Facebook, etc for examples of AI use in code.
And solvers are actually a simpler aspect of the project I am working on. It also includes (or rather aims to include) optimizing compiler with DAE to ODE reduction, advanced numerical debugging etc.
This is why these discussions are pointless - AI works well for some people in some contexts, for others not so much, yet both sides extrapolate their experience as universal.
It seems like developers used to always joke about how much they used stack exchange (even senior devs). Now it seems like there are suddenly so many people who claim to never need any help and can just smoothly bust out beautiful code all day long.
For basically every thing you program, you need to have a really solid understanding of what data structures you will use, and solid general knowledge of the methods you want to implement.
I claim that as a conservative estimate at least 90 % (likely more than 95 %) of what I code at work (and even more for what I code privately) is of this kind.