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@nicuveo@tech.lgbt

Post #1944167

2026-03-04 12:00 UTC

@pmorinerie @jcoglan so, two things on this. On one hand: i agree! arguing against genAI / LLMs in terms of efficiency / productivity is arguing *on their terms*. it's implicitly accepting that those tools are okay to use, despite the fact that even if they were good there would still be a mountain of objections. on the other, i think you've missed the original point that OP was making. :D i don't read the original point as "LLMs are a bad layer of abstraction because they generate bad / bloated code"; i read it as "by their very nature, they are *random* processes: you cannot treat them as just another layer of abstraction, because *every output has to be reviewed*". no matter how bad a compiler is, it is predictable: sure, it will generate inefficient ASM, but it will always generate ASM the same way, while a LLM *by design* cannot.

Replies (1)

  • @pmorinerie@mastodon.xyz 2026-03-04 13:25

    @nicuveo @jcoglan eh, indeed :) The conflit between stochastic GenAIs interfacing with deterministic programming (and operating on data-as-facts) is definitely there. A non-deterministic compiler isn't very useful.

    Open ##1944168