Personalized video feed ranking
Design the recommendation/serving system that builds a personalized home feed of videos for 1B users, choosing from a corpus of billions of items, with a strict <100ms p99 to assemble the ranked feed. Fresh content must surface quickly, watch behavior must feed back into recommendations within minutes, and the system can't re-score billions of items per request. Design the candidate-generation + ranking funnel, the feature/serving infrastructure, and the freshness path.
What a strong answer looks like
Clarify scale and constraints first. Propose a clean component breakdown, then go deep on the hard parts (data model, bottlenecks, consistency, failure modes) and name the trade-offs you are making.
Clarify5:30 left
Estimate5:30 planned
Design16:30 planned
Deep dive13:30 planned
Failure9:00 planned
Which questions mattered is sealed until you submit. Telling you now would just be handing over the edge cases.
Run or narrate your approach, then ask the coach.