You wake up, brew the coffee, open GitHub, and there it is, another pull request on your

open source project. 13,000 lines added, no issue filed first, no discussion. Just here, please

review this for me. Over the past year, GitHub activity has spiked roughly 12 times in a few

short months, and a huge chunk of that signal is landing on the same small group of maintainers who are already stretched very thin.

The curl bug bounty got buried under AI-generated noise, jazz band, the home of Django classics like Pip Tools,

and the Django debug toolbar, hit what its maintainers called in Apocalypse and started sunsetting.

Even Core Python just shipped fresh guidelines on AI

assisted contributions this week. So what does all this actually look like from the receiving

end of the pull requests? On this episode, Paulo Machore joins us to tell the story from

inside the maintainer's chair. Paulo is the director of the Django Software Foundation, an organizer of PyCon

Italy, a Django's Girls coach, and has spent the past year carefully collecting examples of how

AI is reshaping open source contributions, the good, the bad, and the extra fingers.

We dig into his PyCon-US talk on AI-assisted contributions and maintainer load.

Why AI is best understood as an amplifier

rather than a new kind of contributor,

the widely different policies across 86 open-source foundations and projects,

and we ponder whether projects banning AI today

are reacting to last year's models.

This is Talk Python, episode 551 551 recorded May 22nd, 2006.

Yeah. Talk Python to me. Yeah, we ready to roll. Upgrading the code. No fear of getting old.

They sink in the air. New frameworks in sight. Geeky rap on deck. Quark crew. It's time to

unite. We started in pyramid. Cruise in old school lanes, had that stable base, yes, sir.

...