RAG Interview Questions, issue 3, Jul 7, 2026
The Multi-Vector Trap
Senior ML Engineer interview at Anthropic, and the interviewer asks:
“You shipped ColBERT-style multi-vector retrieval because it won on nDCG@10. Two weeks later, p99 latency tripled and your index storage 30x’d. When is multi-vector actually worth that, and what exactly did you lose when you collapsed passages into single vectors before?”
Don’t say: “Multi-vector is more accurate because it keeps more information.”
Why chasing nDCG benchmark wins with ColBERT silently 30x's your index storage, and the hybrid reranking trick senior engineers use to get the exact same precision at a fraction of the footprint.
The full answer, with the mechanism and the arithmetic, is for paid subscribers on Substack.