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[+] 10 points 9 months ago* (last edited 4 weeks ago) (3 children)
  • [–] 18 points 9 months ago (2 children)

    Why does it have to be AI instead of a purpose built, deterministic tool?

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  • [+] 9 points 9 months ago* (last edited 4 weeks ago) (2 children)
  • [–] 20 points 9 months ago (1 child)

    I'd rather use some tool bundled with the framework that outputs code that is up to the current standards and patterns than a tool that will pull defunct patterns from it's training data, make shit up, and make mistakes that easily missed by a reviewer glazing over it

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  • [+] 4 points 9 months ago* (last edited 4 weeks ago) (2 children)
  • [–] 4 points 9 months ago* (1 child)

    I just use https://github.com/cookiecutter/cookiecutter and call it a day. No AI required. Probably saves me a good 4 hours in the beginning of each project.

    Almost all my projects have the same kind of setup nowadays. But thats just work. For personal projects, I use a subset-ish. Theres a custom Admin module that I use to make ALL classes into Django admin models and it takes one import, boom done.

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  • [–] 1 point 9 months ago (1 child)

    “Not worth inventing”? Do you have any idea how insanely expensive LLMs are to run? All for a problem whose solution is basically static text with a few replacements?

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  • [–] [S] 4 points 9 months ago (1 child)

    Back in the day, I used CakePHP to build websites, and it had a tool that could "bake" all the boilerplate code.

    You could use a snippet engine or templates with your editor, but unless you get a lot of reuse out of them, it's probably easier and quicker to use an LLM for the boilerplate.

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  • [–] 8 points 9 months ago

    Easier and quicker, but finding subtle errors in what looks like it should be extremely hard to fuck up code because someone used an LLM for it is getting really fucking old already, and I shudder at all the things like that are surely being missed. "It will be reviewed" is obviously not sufficient

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  • [–] 4 points 9 months ago (1 child)

    All of that can be automated with tools built for the task. None of this is actually that hard to solve at all. We should automate away pain points instead of boiling the world in the hopes that a linguistic, stochastic model can just so happen to accurately predictively generate the tokens you want in order to save a few fucking hours.

    The hubris around this whole topic is astounding to me.

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  • [+] 0 points 9 months ago* (last edited 4 weeks ago) (1 child)
  • [–] 2 points 9 months ago (1 child)

    LLMs do not understand anything. There is no semantic understanding whatsoever. It is merely stochastic generation of tokens according to a probability distribution derived from linguistic correlations in its training data.

    Also, it is incredibly common for engineers at businesses to have their engineers write code to automate away boilerplate and otherwise inefficient processes. Nowhere did I say that automation must always be done via open source tooling (though that is certainly preferable when possible, of course).

    What do you think people and businesses were doing before all of this LLM insanity? Exactly what I'm describing. It's hardly novel or even interesting.

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  • [–] 3 points 9 months ago (1 child)

    Is it possible to use deterministic automation for some boilerplate instead of LLMs?

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