Next Up is designed to help you decide what to watch, read, listen to, resume, or revisit next.
Next Up was designed by a working parent who wanted to spend less time searching and more time enjoying.
We do not believe taste is just an algorithm. Next Up combines user-provided taste signals, saved history, feedback, contextual preferences, and proprietary curation logic to build a more useful cultural profile over time.
We may use underlying AI systems to help parse, organize, summarize, and model taste signals. However, the profile logic, curation framework, recommendation rules, and interpretation layer are built from Next Up's own proprietary knowledge, product design, and cultural intelligence systems.
Your recommendations may consider
- titles you loved, saved, skipped, finished, dropped, or revisited
- books, TV, films, documentaries, podcasts, audiobooks, essays, and other cultural inputs
- creator affinities
- mood, time, format, and service availability
- child-nearby context
- “not for me” feedback
- patterns across repeated behavior
Next Up does not aim to trap you in endless browsing, optimize you for watch time, or flood you with generic recommendations.
The goal
The goal is to help you quickly find something that fits your real life:
- the time you actually have
- the people around you
- the energy you have left
- the services you can access
- the stories, voices, and ideas that tend to stay with you
Feedback
We use feedback such as “Loved,” “Already seen,” “Not now,” “Less like this,” “Not for me,” and “Never show again” to improve future suggestions.
“Never show again” is treated as a hard block for that item unless you remove it later.
Next Up may occasionally be wrong, incomplete, or uncertain. When confidence is lower, we try to make that clear.
Next Up does not replace your taste. It helps you hear it faster.