A human must ultimately take responsibility for all aspects of library code.
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Human Manager Responsibility: The human manager is responsible for reviewing and fully understanding all contributed code.
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Commit Attribution: Commits may be attributed to an agentic AI tool, but all commit messages should include the
@usernameof the human manager who is ultimately responsible for them. For small features, consider squash merges to condense work into a single joint-authored commit to indicate the human associated with any AI contributions. -
Pull Request Review Process: Pull requests involving LLM-assisted code generation or attributed to an agentic AI tool should go through the usual peer review process, with the human manager responsible for the PR completing a pull request code review process first before requesting peer review.
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Effort Balance: The effort contributed by the human manager responsible for LLM-generated code and commits should exceed the effort requested from peer reviewers.
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Limits on extent of Agentic AI use: Agentic AI may be used to perform simple maintenance tasks (e.g., figuring out we need to update a version number) but not to generate new core-library source code.
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Energy Safeguards for Agentic AI use: Agentic AI should not be run automatically without first reaching a consensus among primary developers, and there should be restrictions added to ensure it stops promptly if it is not able to solve a problem.
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In-code citations: Any code that was added via an AI should be clearly marked and ideally include a link to the chat session that generated it.
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Standard of oversight: Contributors and reviewers are expected to have mentally stepped through the code and made sense of it before requesting or approving a review. Exemptions should be requested explicitly where the judged effort tradeoff is not worthwhile. This standard will be subject to further consideration and possible future adjustment.