What does open source maintenance actually look like once a project starts to scale? In this Open Source Friday stream, Ayushman Bhattacharya shares how Pollinations.ai built the systems behind a fast-growing open source AI project. We’ll dig into contributor workflows, paid quests, AI-assisted PR review, app submission pipelines, model curation, and what maintainers really spend their day doing.
Open Source Friday: Building the Contributor Pipeline at Pollinations.ai
www.linkedin.com
Very interesting, the issue with Open Source AI is mainly the lack of processing power but it can be applied in embedded systems where there's no connectivity. Curious: In your workplace, do you use Private AIs like Claude or Open Source Models? Which one fits to your needs?
Looking forward to July 10th with Ayushman Bhattacharya 💯❤️
Excited to attend the session ✨👍
Really excited to talk about how we manage the contributor pipeline, and along with Gwyneth Peña-Siguenza we will have an interesting conversation 💯 looking forward for the event ❤️
The more successful your open source project is. The more you have to deal with bots overwelming your betting process with bogus pushes. In this case the FreeBSD model to open source is superior. Anyone can get the code. But only people with credentials can contribute to it. Pull the bot trick and you get banned from contributing. And since AI can copy entire codebases and "create something new" (which is BS as is derivative), the license becomes moot.