alt Hacker NewsI think the main cause of different views is just the fact that people have very different products and codebases they're working on. Therefore, the requirements and applicability of AI varies a lot, case-by-case. It would be useful if people always explained their exact use cases when making claims one way or another. I understand it's not feasible for many use cases to reveal exact details, but at least some transparency would be great.
I've found AI to be immensely useful in gamedev, mainly UX development, research, and curation. In those areas I let it go quite wild, with mechanical and visual tests for UX, and summaries for research and curation. I've also made skills, custom subagents, hooks, and scripts (all made with AI assistance) to streamline development.
Gamedev is a good example of where AI shines, since the risks of fucking things up are not so big. If I worked on, let's say banking, I'd be much more careful. On my day job, as a data scientist (moving towards product owner) in a large industrial company, I'm much more careful. UX can run on vibes, but anything that touches data processing or business logic needs to be looked at by a human, row by row. Depending on use cases, it may be fine to look at only the tests. The main problem is that there's so much stuff to review, and maybe 98% of it is fine. It's then very boring to try to spot the 2%. I don't have good solutions for that yet, and idk if anyone does.
> It would be useful if people always explained their exact use cases when making claims one way or another. I understand it's not feasible for many use cases to reveal exact details,
It would be useful if people _ever_ explained the use cases. Even Anthropic when they're publishing their materials are hand wavey about this.
> Gamedev is a good example of where AI shines, since the risks of fucking things up are not so big
I couldn't disagree more. I run an engineering team in GameDev, and AI is great at making a gigantic mess. It's great for generating a lot of code, but the minute that doesn't do what you want it to, you now need to go back and learn _everything_ that it's generated. And IME, doing that is as bad as having just written it yourself in the first place.
> he main problem is that there's so much stuff to review, and maybe 98% of it is fine. It's then very boring to try to spot the 2%. I don't have good solutions for that yet, and idk if anyone does.
I tentatively agree here, except I've found about 50% of it is "fine", 40% of it is "this works but isn't really what I want to put into my product" and 10% is "absolutely not".