Contributor Policy

The RS AI Learning Lab may invite learners, writers, creators, interns, mentors, or future consultants to help build learning materials, examples, activities, labs, handouts, case studies, and review notes.

This must be opportunity-building, not extraction.

Core Principle

Contribution must be transparent, scoped, reviewed, credited where appropriate, and paid when work is assigned, used commercially, or becomes part of RS product development.

Contributor Work Must Include

• a clear brief
• expected deliverable
• audience
• constraints
• review criteria
• owner or reviewer
• credit and payment notes
• safety and privacy review expectation

Credit And Payment Defaults

• Exploratory learner exercises can remain personal practice unless RS asks to use them.
• Assigned work should have clear payment terms before work begins.
• Work used commercially or incorporated into RS product development should be paid unless a separate written agreement says otherwise.
• Portfolio value should be stated plainly, including what the contributor can point to afterward.
• Credit should be given where appropriate and safe, but privacy, client confidentiality, and contributor preference matter.

Review And Approval

No contributor artifact is approved for external or commercial use until RS has reviewed it for:

• learner usefulness
• tone
• accessibility
• factual reliability
• privacy and safety
• fit with RS principles
• scope and licensing clarity

GitHub Workflow

Use GitHub Issues for assignment, questions, status, and review. A proposed lab begins as a Lab Activity Issue; once triaged and assigned, its durable package belongs in labs/ and is submitted through a linked pull request. Use Markdown files in contributor-briefs/ when a durable contributor brief should remain part of the project source.

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Source: contributor-policy.md