Like others have mentioned, I think the premise of looking at the most popular few projects (pypi.org currently lists 771,120 projects) on pypi as any sort of proxy for AI coding is terribly misguided/unrepresentative and that almost no one is going to be packaging up their vibe-coded projects for distribution on pypi.

That being said, I've personally put 3 up recently (more than I've published in total). I'm sure they have close to zero downloads (why would they? they're brand new, solve my own problems, I'm not interested in marketing them or supporting them, they're just shared because they might be useful to others) so they wouldn't show up in their review. 2 of these are pretty meaty projects that would have taken weeks if not months of work but instead have been largely just built over a weekend or a few days. I'd say it's not just the speed, but that w/o the lowered effort, these projects just wouldn't ever have crossed the effort/need bar of ever being started.

I've probably coded 50-100X more AI-assisted code that will never go to pypi, even as someone that has released pypi packages before (which already puts me in a tiny minority of programmers, much less regular people that would even think about uploading a pypi project).

For those interested in the scope of the recent projects:

https://pypi.org/project/realitycheck/ - first pypi: Jan 21 - 57K SLoC - "weekend" project that kept growing. It's a framework that leverages agentic coding tools like Codex/Claude Code to do rigorous, systematic analysis of claims, sources, predictions, and argument chains.It has 400+ tests, and does basically everything I want it to do now. The repo has 20 stars and I'd estimate only a handful of people are using it.

https://pypi.org/project/tweetxvault/ - first pypi: Mar 16 - 29K SLoC - another weekend project (followup on a second weekend). This project is a tool for archiving your Twitter/X bookmarks, likes, and tweets into a local db, with support for importing from archives and letting you search through them. I actually found 3 or 4 other AI-coded projects that didn't do quite what I wanted so it I built my own. This repo has 4 stars, although a friend submitted a PR and mentioned it solved exactly their problem and saved them from having to build it themselves, so that was nice and justifies publishing for me.

https://pypi.org/project/batterylog/ - first pypi: Mar 22 - 857 SLoC - this project is actually something I wrote (and have been using daily) 3-4 years ago, but never bothered to properly package up - it tracks how much battery is drained by your laptop when asleep and it's basically the bare minimum script/installer to be useful. I never bothered to package it up b/c quite frankly, manual pypi releases are enough of a PITA to not bother, but LLMs now basically make it a matter of saying "cut a release," so when I wanted to add a new feature, I packaged it up as well, which I would never have done this otherwise. This repo has 42 stars and a few forks, although probably 0 downloads from pypi.

(I've spent the past couple years heavily using AI-assisted workflows, and only in the past few months (post Opus 4.6, GPT-5.2) would I have even considered AI tools reliable enough to consider trusting them to push new packages to pypi.)