May 24, 2026
Slop Wars: Bug Report Edition
Building Pi with Pi
AI bug reports are getting roasted as coders beg: please just tell us what broke
TLDR: Pi’s creator says AI-written bug reports are making software fixing harder, because they sound confident while often being wrong. Commenters loved the irony, roasting the “slop” problem, arguing over whether machines have agency, and treating the whole thing like a robot-made own goal.
A software maker says he’s now using his own artificial intelligence tool, Pi, to help build Pi itself — and the internet immediately turned the whole thing into a drama about robot-written nonsense. His big complaint is painfully relatable even to non-coders: people report a problem, but instead of simply saying what happened, they run it through an AI helper first. The result, he says, is a bloated, overconfident mess full of guesses, fake explanations, and very confident wrong ideas. In his view, that’s actually worse than no explanation at all.
The comment section wasted no time sharpening the knives. One reader delivered the most savage summary possible: the tool speeding up low-quality output is now suffering from its own low-quality output. Another pounced on the author’s favorite word, “clanker,” arguing that if humans keep handing work to machines, then yes, the machines do in fact have agency. And then came the philosophical drive-by: one commenter mocked the whole setup as a human demanding a machine “independently verify” facts that the human didn’t bother to verify first. Ouch.
But this wasn’t all doom and gloom. There was also peak internet energy: one person got distracted by the font in the last image, while another joked that “yet another Lord of the Rings AI company” was not on their bingo card. So yes, the article is about better bug reports — but the real spectacle is the crowd gleefully dunking on AI slop, word choices, and the absurdity of using a robot to clean up robot-made messes.
Key Points
- •Armin Ronacher says Pi is now part of Earendil and reflects on using Pi to help build Pi itself.
- •The article argues that issue trackers now serve both human maintainers and agent workflows, because issue descriptions are used as prompt inputs.
- •Ronacher says many issue reports are increasingly AI-rewritten, with confident but inaccurate diagnoses that create extra work.
- •He states that Pi can be misled by incorrect issue text because it tends to treat the issue body as evidence.
- •The article recommends keeping issue reports focused on direct human observations: command run, expected result, actual result, and exact error or log.