You wake up, brew the coffee, open GitHub, and there it is. Another pull request on your open source project. Thirteen thousand lines added. No issue filed first. No discussion. Just "here, please review this for me."

Over the past year, GitHub activity has spiked roughly twelve times in a few short months, and a huge chunk of that signal is landing on the same small group of maintainers who were already stretched thin. The curl bug bounty got buried under AI-generated noise. Jazzband, the home of Django classics like pip-tools and the Django debug toolbar, hit what its maintainer called an "apocalypse" and started sunsetting. Even CPython just shipped fresh guidelines on AI-assisted contributions this week.

So what does all of this actually look like from the receiving end of the pull request?

On this episode, Paolo Melchiorre joins us to tell that story from inside the maintainer's chair. Paolo is a director of the Django Software Foundation, an organizer of PyCon Italy, a Django Girls coach, and he 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 wildly different policies across 86 open source foundations, whether projects banning AI today are reacting to last year's models.

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Links from the show

Paolo Melchiorre: github.com

DSF: www.djangoproject.com

djangonaut-space: djangonaut.space

PyCon Italia: 2026.pycon.it

uDjango: github.com

My PyCon US 2026 post: www.paulox.net

AI-Assisted Contributions and Maintainer Load: www.paulox.net

Senior Engineer Tries Vibe Coding: www.youtube.com

Code Rabbit AI PR Reviews: www.coderabbit.ai

GitHub Usage Graphs: github.blog

Update on CPython's AI Policies: fosstodon.org

High-Quality Chaos from Curl: daniel.haxx.se

The Generative AI Policy Landscape in Open Source: redmonk.com

Watch this episode on YouTube: youtube.com

Episode #550 deep-dive: talkpython.fm/550

Episode transcripts: talkpython.fm

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