Generative AI

Generative AIhasevolved rapidly over the past decade and will continue inthefuture.

Their overuse can also be problematic, such as generationofincorrect code, inaccurate documentation, and unneeded code churn.

Discretion, good judgement, and critical thinking **must** beusedwhen opening issues and pull requests.

Generative AItools haveevolved rapidly, and their suggested results can be helpful. As with using any tool,theresulting contribution is

churn. Discretion, good judgment, and critical thinking are the foundationofall good contributions, regardless of the

toolsusedin their creation.

Acceptable uses

Maintainers may close issues and PRs that are not useful or productive, including

those that are fully generated by AI. If a contributor repeatedly opens unproductive

issues or PRs, they may be blocked.

Considerations for success

- While AI assisted tools such as autocompletion can enhance productivity, they sometimes rewrite entire code blocks instead of making small, focused edits.

This can make it more difficult to review changes and to fully understand both the original intent of the code and the rationale behind the new modifications.

Maintaining consistency with the original code helps preserve clarity, traceability, and meaningful reviews and also helps us avoid unnecessary code churn.

- Sometimes AI assisted tools make failing unit tests pass by altering or bypassing the tests rather than addressing the underlying problem in the code.

Such changes do not represent a real fix. Authors must review the work done by AI tooling in detail to ensure it actually makes sense before proposing it as a PR.

- Keep the following principles for the quality of your contributions in mind whether you use generative AI or not:

- Consider whether the change is necessary

- Make minimal, focused changes

- Follow existing coding style and patterns

- Write tests that exercise the change