Chat Endpoint 2 Second Question Explained
This worked AI Engineer Interview practice question tests Problem Framing. Try the answer first, then review why A is the best choice.
Short answer
The correct answer is A. Which pipeline stage — queueing, retrieval, prompt build, first token, generation — actually owns the tail..
A smaller model only helps if inference is the bottleneck; a 10× p50→p95 gap usually points at queueing, retrieval, or long-input cohorts, so you decompose latency by stage first. The key is to match the exact action in the prompt to the tool, command, or concept that performs that action directly. Here, A. Which pipeline stage — queueing, retrieval, prompt build, first token, generation — actually owns the tail. is the only option that satisfies the scenario without adding unrelated behavior.
The Question
A chat endpoint has a 2-second p50 but a 19-second p95. Product wants to switch to a smaller model today. What do you establish before choosing any fix?
Why A is correct
A smaller model only helps if inference is the bottleneck; a 10× p50→p95 gap usually points at queueing, retrieval, or long-input cohorts, so you decompose latency by stage first. The key is to match the exact action in the prompt to the tool, command, or concept that performs that action directly. Here, A. Which pipeline stage — queueing, retrieval, prompt build, first token, generation — actually owns the tail. is the only option that satisfies the scenario without adding unrelated behavior.
Why the other options are wrong
Option B does not match the requirement in the prompt. The correct answer is A because A smaller model only helps if inference is the bottleneck; a 10× p50→p95 gap usually points at queueing, retrieval, or long-input cohorts, so you decompose latency by stage first.
Option C does not match the requirement in the prompt. The correct answer is A because A smaller model only helps if inference is the bottleneck; a 10× p50→p95 gap usually points at queueing, retrieval, or long-input cohorts, so you decompose latency by stage first.
Option D does not match the requirement in the prompt. The correct answer is A because A smaller model only helps if inference is the bottleneck; a 10× p50→p95 gap usually points at queueing, retrieval, or long-input cohorts, so you decompose latency by stage first.
Key idea: Problem Framing
Every question is a production situation an AI engineer interviewer can put to you: a failing endpoint, a cost spike, an agent that loops, an eval that disagrees with users. The best answer is almost always the one that measures or contains the problem before it changes the model or the prompt. If you miss a question, note which habit it tests: decompose before you fix, put the security boundary where the side effect happens, and trust an eval only after you check what it covers. The 12 open-ended questions with answer guides are at aijobprep.app/questions/ai-engineer.html.
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