@hongminhee@hollo.social · Reply to silverpill

@silverpill @phnt That's a fair clarification, and worth being precise about on my end too.

I'm not arguing for historical inevitability—I don't think that's a useful frame for anyone here. What I was saying is closer to a personal read of the current situation: a lot of developers already depend on LLMs in their day-to-day work, and that number seems to be growing quickly. That's an observation, not a law of history, and I could be wrong about where it leads.

The NFT comparison is interesting and I won't dismiss it. My intuition is that LLMs are a different kind of thing—they've become embedded in actual workflows in ways NFTs never were—but I hold that loosely. Technologies do fail in unexpected ways.

What I'm more confident about is the narrower point: maintainers have real authority over their own projects, and I think there's more room in that space than “accept everything” or “reject all AI-assisted contributions.” My own approach with Fedify has been to set conditions rather than draw a line: disclose what you used, show you've actually tested it. Whether that's the right call, others can judge: https://github.com/fedify-dev/fedify/blob/main/AI_POLICY.md.

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fedify/AI_POLICY.md at main · fedify-dev/fedify

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2 replies

@lain@lain.com · Reply to 洪 民憙 (Hong Minhee) :nonbinary:
@hongminhee @phnt @silverpill i have no idea how anyone who has used them can think that LLMs aren't here to stay. open models are available and inference is cheap and plentiful. those models (like glm-5.2) are already at the level of the average developer, but cost much less. frontier models are better than most programmers you know. and that's just the programming part, they can do much every other white collar job as well. even if openai, spacex, anthropic and everyone else died tomorrow, people would just run kimi 3 and glm-5.2 and have an experience that would have been unthinkable even a year ago.