The text explores the concept of A/B testing and experimentation across various entities beyond individual users, with a focus on how companies like Facebook utilize different levels of feature rollouts. It highlights the complexities of experimenting not only at the user level but also at the group, page, or organization level, noting that the same user may experience different features based on the entity they interact with. Tools like Statsig help companies run these experiments by allowing the use of Custom IDs to ensure consistent experiences across specific groups or entities. This approach is mirrored in other enterprise tools like Figma, Notion, and Amplitude, which also implement experiments across various organizational levels. The text underscores the importance of choosing the appropriate unit type for experiments to maintain consistency and reliability, and mentions the implementation of tools like GK::forVC() and GK::forID() to manage variant checks in these experiments.