A concise explainer of the standard four-stage architecture used in most modern recommendation and ranking systems: retrieval, scoring, ordering, and feedback.
It walks through how these stages connect in production systems like search, feeds, and content recommendations, with diagrams and examples.
Part of a five-part series exploring each stage in more detail this week.
Curious how others here are evolving these pipelines. Are you moving toward more unified (retrieval+scoring) models, or keeping stages separate for latency and control?
