I agree as well. Especially in the context of recommendation systems, the decoupling of retrieval from a heavy ranker has a lot of benefits. It allows for 1) faster experimentation, and 2) the use of different retrieval sources. In reality, the retrieval might consist of a healthy mix of different algorithms (collaborative filtering, personalized page rank, word2vec/2tower embeddings, popular items near the user, etc.) and fallback heuristics

It allows faster experimentation because you can't do things like partial embedding updates and reasonable schema migrations on your vector search index - if you could, you'd experiment in retrieval... and with better retrieval you don't have to move 100s or 1000s of candidates from a database and pay a ton for a ranker inference on every query (not even mentioning the latency impact of that).