How would you answer an interview scenario involving Vector search and similarity?

For an interview scenario involving Vector search and similarity, I would first clarify the business goal, scale, constraints, and the failure or quality attribute the interviewer wants to explore. Vector search retrieves items whose embeddings are close to the query embedding according to a similarity metric such as cosine similarity. I would then explain the main alternatives and tradeoffs, identify likely failure modes, and describe how I would validate the solution through testing, observability, security controls, and recovery or rollback planning.