Reviews policy

How we surface ratings and reviews on classes.

Two kinds of reviews

Why we do this

A brand-new class with zero reviews looks broken even when the content is strong. Synthetic samples let new classes display the same UX as established ones. As real learners arrive, their reviews push generated ones down and eventually replace them.

Disclosure

Every course page shows this disclosure beneath its reviews. We don't claim generated samples are real or attribute them to specific people you could verify. Aggregate rating numbers are explicitly marked as preliminary until verified-learner reviews dominate.

FTC alignment

This approach is calibrated to the FTC's 2024 guidance on AI-generated and incentivised reviews: never claim a synthetic review is from a real customer, and never bury negative reviews. We don't.