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Code RoomCold-start recommendations
MediumPrep Room Coding #4608

Cold-start recommendations

System designML systemsMid–Senior~35 min

Design a personalization cold-start system for a marketplace homepage. The hard part is the cold-start edges: brand-new users (no history) and brand-new items (no interactions) must still get reasonable, relevant recommendations from their first session, while established users get fully personalized results. Scale is ~10M daily users and a catalog of ~5M items with thousands of new items added daily. Homepage must render in ~150ms, and you need both new users and new items to start accumulating useful signal quickly rather than being stuck in a chicken-and-egg trap.

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.

Clarify4:00 left
Estimate4:00 planned
Design11:30 planned
Deep dive9:30 planned
Failure6:00 planned
0:00
Which questions mattered is sealed until you submit. Telling you now would just be handing over the edge cases.