I don’t knowingly use AI at all in my person life and projects (I say ‘knowingly’ since many products have it shoved inside now, but I disable all I see). At work, we have AI code reviews which, as a concept, I think is fine and useful.
Issue triage, code exploration, extracting information from disparate sources, first pass code review. There are loads of use cases that it’s potentially useful.
For me it’s a lot better at extracting the requirements for a CPU feature from a 10,000 page architecture reference manual than I am.
Quite; I just set a (locally hosted) LLM off writing the tickets for implementing all the opcodes in a simple device emulator, based on grovelling through datasheets and documentation. Whether the tickets get implemented by an AI or a human, it’s a timesaver having the AI do it, and the tickets will be better written than I would have done.
Everyone railing against this also overlooks the reality of professional software development: professional software is developed 5% by skilled, trained Software Engineers, and 95% by code monkeys who shotgun copypasta from Stack Overflow until it works. Even if we extremely generously assume that the hardcore “never use AI” Lemmy brigade are in the 5% (and not, more likely the 95% drowning in their own Dunning Kruger,) the “but AIs produce unreadable code and make mistakes” threat isn’t putting off anyone who’s ever actually had to hire a significantly sized development team.
This is why I don’t use it for coding at all.
Yes, the obvious solution is to avoid it. I use it only for the most boilerplatey things. Anything else, I want to make sure I can still do it myself.
I don’t knowingly use AI at all in my person life and projects (I say ‘knowingly’ since many products have it shoved inside now, but I disable all I see). At work, we have AI code reviews which, as a concept, I think is fine and useful.
IMO that’s totally fine and appropriate
Issue triage, code exploration, extracting information from disparate sources, first pass code review. There are loads of use cases that it’s potentially useful.
For me it’s a lot better at extracting the requirements for a CPU feature from a 10,000 page architecture reference manual than I am.
Quite; I just set a (locally hosted) LLM off writing the tickets for implementing all the opcodes in a simple device emulator, based on grovelling through datasheets and documentation. Whether the tickets get implemented by an AI or a human, it’s a timesaver having the AI do it, and the tickets will be better written than I would have done.
Everyone railing against this also overlooks the reality of professional software development: professional software is developed 5% by skilled, trained Software Engineers, and 95% by code monkeys who shotgun copypasta from Stack Overflow until it works. Even if we extremely generously assume that the hardcore “never use AI” Lemmy brigade are in the 5% (and not, more likely the 95% drowning in their own Dunning Kruger,) the “but AIs produce unreadable code and make mistakes” threat isn’t putting off anyone who’s ever actually had to hire a significantly sized development team.