Define the AI-assisted authoring and expert-review policy
Make the iterative authoring process credible by documenting source, testing, learner-feedback, and expert-review expectations.
Depends on: AIINFRA-002
Outcome
Readers and contributors can tell how material moves from generated draft to studied, tested, reviewed, and maintained course content.
Why it matters
The value of the course is not that a model can produce a large volume of prose. It is the repeated loop of technical study, learner annotations, primary-source checks, experiments, and expert criticism that turns drafts into durable explanations.
Deliverables
- Define visible maturity states for course material.
- Specify primary-source and citation expectations.
- Document the browser-annotation review loop and expert handoff format.
- Define how corrections, disputes, obsolete material, and vendor-specific claims are handled.
Acceptance criteria
- A reader can distinguish generated draft, author-reviewed, lab-verified, and expert-reviewed material.
- Review credit and remaining uncertainty can be represented without implying endorsement of the whole course.
- Technical claims with meaningful change risk have a maintenance path.
- The policy is short enough to be followed consistently.