source: simon willison: quoting armin ronacher
level: technical
armin ronacher, creator of flask and a prominent open source developer, describes a growing frustration with ai-generated issue reports. he says people submit problems not in their own voice, after running them through a language model that rewrites and expands the text. the result is often a mess: the ai adds confident but inaccurate conclusions, guesses at root causes, invents minimal reproductions that do not work, suggests irrelevant implementation strategies, and lists error classes that may not apply.
the core problem is that the human observation gets buried under layers of ai-generated noise. instead of a clear statement of what command was run, what was expected, what actually happened, and the exact error or log output, maintainers receive long, rambling reports full of speculation. this wastes time and makes it harder to identify and fix real bugs. ronacher says he increasingly wants issue reports condensed back to the raw human observation.
this trend reflects a broader challenge in ai-assisted software development. while language models can help draft text, poorly prompted use in technical contexts often degrades information quality. for open source projects that rely on clear communication between users and maintainers, ai slop in bug reports can slow down development and increase burnout. ronacher's call is for humans to keep their own voice in issue reports and let the facts speak for themselves.
why it matters: ai-generated noise in bug reports can hide real problems and slow down open source development, making it harder for data science and ai tools to improve reliably.