Two related accounts describe why AI can rapidly generate an app’s interface and code, yet shipping still takes time and can fail. In the first account, the author builds a one-screen convenience-store deals app quickly, but the screen is unusable because it lacks real, regularly updated deal data. Convenience-store promotions are not available as a neat, consistent API, so the needed information is scattered across brands and store systems. The author highlights that deal accuracy must be maintained week by week; missing an update makes the app show ended offers, eroding trust. Adding “sticky” features like favorites, alerts, and rewards also expands the work, because login introduces personal-data obligations and rewards add additional rules and compliance steps.

In the second account, the author explains that passing app review is not mainly about whether the code runs. Review focuses on whether the app includes required policy and consent elements for the features it implements. Each feature can trigger distinct checks—privacy policies and consent for login and location, opt-ins for promotional notifications, and specific disclosures for rewards or points. The author also notes that templated or placeholder policy pages can be rejected, and marketing copy with absolute claims may trigger additional scrutiny. Together, the sources argue that AI helps with step one, but shipping depends on data ownership, maintenance, and policy design.