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@MaddieM4@raphus.social

Post #4260737

2026-07-31 01:01 UTC

LLMs inspire or surface a *lot* of lotus-eating incuriosity, but the thing I keep coming back to in particular is that they give you a perceived freedom to never address a root cause ever again, which allows you to live with the problems you can't practically solve. "I use AI to summarize my emails!" Because it's normal to get too many emails from too many people with too little substance, and now that can be normal-er! "I use AI to find the important parts of a large specification." Why was it large and unfocused with no human summary by the authors? In corporate environments, these problems feel impossible to solve, only paper over in a way that allows them to become even worse, because these dysfunctions are like goldfish - they grow to the size of the bowl. A bigger bowl only helps in the most temporary sense. There's a reason people find them less useful for things like summarizing a breakup text. Things that matter happen outside of process doomerism and bureaucratic complacency.

Replies (1)

  • @MaddieM4@raphus.social 2026-07-31 01:16

    Honestly one of the most useful games you can form a habit of, lately, is finding the root cause that a given LLM use case is cynically avoiding. Feel free to post your own! I'll do one more myself, though. "I use AI to handle the boilerplate when writing software." Why was that boilerplate necessary, instead of handled by a deterministic, maintainable, ideally open-source abstraction? Would things like SDL be created, if LLMs had allowed you to bodge an individual solution from stolen snippets with no community maintenance back then? Where do we expect the SDLs of tomorrow to come from?

    Open ##4260736