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Apalache AI Usage Policy

The Apalache project has strict rules for AI usage:

  • All AI usage in any form must be disclosed. You must state the tool you used (e.g. Codex, Claude Code, Cursor, Copilot) along with the extent that the work was AI-assisted.

  • The human-in-the-loop must fully understand all code. If you can't explain what your changes do and how they interact with the greater system without the aid of AI tools, do not contribute to this project.

    In particular, if you are new to Scala, you must be able to explain all programming constructs in your contribution. AI tools are great helpers for learning. Use them to understand your code. The project maintainers do not have to remember all of Scala by heart. Hence, we tend to use the common subset of the language and idioms that are understood by humans.

  • Issues and discussions must be written by humans. AI tools are good at producing lengthy prose, but this prose is hard to read for humans. We prefer text that demonstrates human reasoning. It is okay to have spelling and grammar mistakes, as long as you have put some thinking into your writing.

    If you use AI to do research, you may quote the results of that research in a clearly marked blockquote. However, you must verify the results before quoting them, and you must trim the results down to the relevant information.

  • Descriptions of Pull Requests must be written by humans. Pull requests should specify: the intent of the change, the key design decisions, the system parts affected, and the key changes (briefly). The size of the PR text must be proportional to the size of the change. A 10-line change does not need a 5-page description.

  • No AI-generated media is allowed (art, images, videos, audio, etc.). Text and code are the only acceptable AI-generated content, per the other rules in this policy.

  • The number of active Pull Requests is limited. It takes effort to open a high-quality Pull Request. You have to prioritize your contributions and submit the important ones first.

  • Signed-off-by and Developer Certificate of Origin. AI agents MUST NOT add Signed-off-by tags. Only humans can legally certify the Developer Certificate of Origin (DCO). The human submitter is responsible for:

    • Reviewing all AI-generated code

    • Ensuring compliance with licensing requirements

    • Adding their own Signed-off-by tag to certify the DCO

    • Taking full responsibility for the contribution

    Moreover, read the LF Guidance on Generative AI to understand the copyright and licensing implications of using AI tools.

The above rules apply only to outside contributions to Apalache. Maintainers are exempt from these rules and may use AI tools at their discretion. They have proven themselves trustworthy to apply good judgment.

There are Humans Here

Please remember that Apalache is maintained by humans. About 99% of the code has been written by humans. This means that many design and coding decisions do not follow the canned recipes of the AI tools. Due to that, the AI tools may fail to understand the intent behind the code.

Every discussion, issue, and pull request is read and reviewed by humans (and sometimes machines, too). It is a boundary point at which people interact with each other and the work done. It is rude and disrespectful to approach this boundary with low-effort, unqualified work, since it puts the burden of validation on the maintainers. Most of the time, the maintainers are not paid for doing this work, and they aim at improving the project quality, not reading the inference of AI tools.

AI is Welcome Here

The active maintainers of Apalache are using the AI tools themselves. We embrace the use of AI. We are careful about the Apalache design and code, as almost all of the code has been written by humans, who put plenty of their thought into it.

Our reason for the strict AI policy is not due to an anti-AI stance. We understand that many external contributors are trying to help the project. We also know that it is tempting to shoot an AI tool at a problem and see it "solved". Unfortunately, the AI tools do not have understanding of the impact of their code. We often see the code that may even solve the issue, but it is not properly integrated into the system, nor is it properly tested. As a result, the maintainers have to spend hours of their time on fixing code that was generated in 10 minutes.

References

This policy derives from the following AI policies and guidelines: