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Do you know what's not accessible?

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Gli ultimi otto messaggi ricevuti dalla Federazione
  • @matt "quantity has a quality all its own". Maybe I can write better code, given sufficient time. I can certainly write more concise code (especially in Perl).

    But, the models write code an order of magnitude faster than I can, and they can write code 24/7. And, honestly, it's pretty good code, most of the time.

    It's still true that the hardest part is deciding what to make rather than making it, but it's drastically easier to write software now with the AI than doing it myself.

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  • @swelljoe yup. But if you use it as a tool to assist you, you can assist yourself. I found that out yesterday.

    https://berryvilleiml.com/2026/02/18/using-gemini-in-the-silver-bullet-reboot/

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  • @swelljoe That's interesting considering that if I'm not mistaken (based on your work on Webmin/Virtualmin), one of your best languages is Perl. I never seriously got into Perl, but it has a reputation for being quite expressive. So in theory, you should be able to express what you want directly in the language. It feels wrong that giving instructions to an LLM, in ambiguous natural language, and having it grind away, is kicking your ass even in a language like Perl. Like a failure of PL design.

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  • @clayote I mean, there are still problems it can't solve, but that set is much smaller than you would think if you last looked at it seriously any time up until a few months ago. The models now can search the web, instrument software so they can test without human intervention, and plan quite large/complicated projects for implementation across several context windows.

    When driven by an expert, there is very little it can't do, and it does it all very, very, rapidly.

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  • @clayote it is quite wrong, as of October of last year, when the current crop of models arrived. As of Opus 4.5, Codex 5.2, and Gemini 3, when used in an agentic context (e.g. Claude Code), they're not limited to simple/repetitive code or code that is prominent in the training data.

    The training data is "the entire internet and all of public Github", so it knows every language, every framework. Yeah, it's better at simple CRUD apps in TypeScript, but it also kicks my ass in my best languages.

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  • @clayote @swelljoe I'd say that was true not that long ago, but not necessarily now. More likely to be true of those people who don't even look at the output, which I think is atrocious.

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  • @noplasticshower yeah, I'm confident that many, if not all, of the major models have ingested the thousands of posts I've made to the forum I maintain for the OSS projects I work on. I feel ambivalent about that. On one hand, if someone is asking ChatGPT for help with my software, I'd rather it give reasonable answers than dangerous ones.

    But, also, it sucks that the way it does that kind of thing is DDoSing my websites periodically and blatantly disregarding copyright or licenses.

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  • @swelljoe As a non-user of AI (lucky), my impression was that in the areas it works well in -- repetitive codebases that resemble ones in the training dataset -- the productivity increase also incurs technical debt at a rate higher than if you'd gotten some junior coders to do it; is that wrong?

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