Imagine taking the lightweight, privacy-focused appeal of Linux and completely ruining it by hardwiring AI models straight into the OS. Nobody is switching from Windows for more forced AI features.

  • Victor@lemmy.world
    2·
    2 days ago

    An excavator can also lift rocks that I can’t. But that’s really beside the point.

    It doesn’t really matter which analogy you use, the fact is that I can do what an LLM can do, in my field. I can probably do a better job, because I know more current web APIs than an LLM has had time to train on because of limited human output.

    You don’t get faster results with more developers though. You don’t make a baby in one month with 9 mothers either. You might have seen a small increase in development time with more than one dev on a single project but that doesn’t scale past more than a handful of devs, usually. At least not per feature.

    • chaosCruiser@futurology.todayEnglish
      2·
      1 day ago

      Actually, that’s a good point. Proper programmers are impossible to replace. LLMs have the greatest impact for people who can only write bad code slowly or not at all. They will see a huge boost in output. However, they are also least qualified to take care of quality control, so the output ends up being 100% slop code. People like that will end up slopping together software projects that are impossible to maintain.

      • Victor@lemmy.world
        2·
        1 day ago

        And it’s super worrying, because everyone I know and almost every colleague I have is suckling on the LLM teets right now, but they don’t realize that their enthusiasm affects the youth that we will have to rely on to maintain our projects once we retire. They’re gonna be so bad at it.

        Adopting and maintaining software is hard enough as a good programmer. 😅😅

        • chaosCruiser@futurology.todayEnglish
          2·
          1 day ago

          The current generation is throwing a massive slop grenade at the next. Here, catch!

          Technically, you can use an LLM to learn what code does, how a function works, why some convoluted workarounds are necessary, etc. If you really take the time to do that, you should also add lots of relevant comments to the code, something the LLM certainly won’t do. When you look at the code two weeks later, you’ll still be able to debug it on your own or tell an LLM to carry out very specific tasks for you. Either way, this route takes time and effort, which is why most won’t do it. The temptation to skip vital steps is too great. That’s how we’re currently driving to a software maintenance dead end.

          Sooner or later, the code is such a mess that you can’t fix it by throwing more AI at it. Humans have to understand exactly what the code does and why it works that way. When people start dealing with these slop grenades every month, they realise how important it is to have proper guidelines about using LLMs responsibly. It’s about time someone starts teaching these guidelines that haven’t been written yet