Personalization is a ranking problem — architecture makes it work

Personalization works best when it is treated as a real-time ranking problem, not a set of isolated recommendation features.

A unified ranking architecture can combine user intent, item data, context, availability, and business goals at query time.

Fragmented stacks with search, vector retrieval, rerankers, feature stores, and rule engines often miss live signals and produce stale results.

The article says this architectural view explains why many systems feel irrelevant, slower, and less consistent.