I’ve used spicy auto-complete, as well as agents running in my IDE, in my CLI, or on GitHub’s server-side. I’ve been experimenting enough with LLM/AI-driven programming to have an opinion on it. And it kind of sucks.
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
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.
If it’s as minimal as possible, then the responsible play is to write it thoughtfully and intentionally rather than have something that can make subtle errors to slip through reviews.
“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?
If it’s 90% boilerplate like you were saying above, how flexible does it need to be, really? If it only needs to get 90% there, surely a general-purpose scaffolding tool could do the job just as well.
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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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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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If it’s as minimal as possible, then the responsible play is to write it thoughtfully and intentionally rather than have something that can make subtle errors to slip through reviews.
“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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If it’s 90% boilerplate like you were saying above, how flexible does it need to be, really? If it only needs to get 90% there, surely a general-purpose scaffolding tool could do the job just as well.