Search & discovery

Search and feed discovery depend on multiple candidate generators and relevance signals to pull a manageable set of items from a huge corpus before ranking; relevance improvements require offline checks, human review, and traffic evaluation.

PAINSearch and feed experiences must choose a small, relevant set of items from a very large content corpus; prior heuristic candidate generators and weaker relevance signals make it harder to fulfill user intent at scale.