LLM Thoughts (mine)

A developer’s essay on disliking LLMs that is less about the reasons, which the author takes as known, than about why the conversation goes wrong.

The ethical case (training on the whole internet, land for datacentres, harvesting user data) is sound, the author says, but works like the case for veganism: a good reason for your own choices and a weak tool for changing anyone else’s. Arguing by proxy makes it worse. People who object on ethical grounds argue about code quality or licensing instead, and project AI-policy debates turn into everyone talking past each other.

The everyday complaint is annoyance. LLM-written bug reports and pull requests hand the work to the maintainers who have to read them. The author also finds the tools worryingly habit-forming, a reprise of the social-media playbook aimed at work time, and suspects “AI is inevitable” is partly the voice of people who can no longer code without one. Output quality doesn’t change the author’s mind either way. A narrower use, a real program with a small language model only filling in its inputs, would bother them far less.