Principles for sustaining open source in the age of generative AI
AI has changed how we write code, but open source remains a human system built on trust, accountability, and shared stewardship. These principles guide the responsible use of AI in open source communities.
Every contribution carries your name. Take the time to understand the intent, verify the correctness, and stand behind the outcome of what you submit. Accountability for the codebase is a human responsibility that cannot be delegated to a model.
Code that merely compiles is not code that is proven safe. Every change requires evidence proportional to its risk. Whether AI helped you write it or not, always provide tests, reproduction steps, and security checks.
Every pull request costs human attention, which is the scarcest resource in open source. Just because AI allows you to generate code quickly does not mean you should submit it all at once. Prioritize quality over quantity to make every submission worth a maintainer’s time.
Because AI can scale code output faster than human attention can process it, you need to compensate with clear artifacts. Write meaningful commit messages, provide architecture notes, and map out your logic. The more code you generate, the more context you owe the community.
While AI is a great tool for drafting code, every issue, comment, and code review should be written in your own voice. Do not let a model handle your community interactions. Trust, collaboration, and resolving disputes require real human connection.
AI models are built on the historical work of the open-source community. Be mindful of licensing boundaries and avoid blindly copying large, opaque blocks of generated code that might infringe on the rights of others. Respect the origins of the code you contribute.
This list will evolve. The manifesto is open source and open for contributions.
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