Practiced one out loud? Paste your answer into the free self-check and get a score in 30 seconds
What the interviewer is testing
Whether you can explain the root cause in one sentence, give layered mitigations that a production system can actually use, and say how you would measure the problem rather than only describe it.
Answer framework
- Cause: the model is trained to produce plausible continuations, not to verify facts, and it has no built-in signal for what it does not know.
- Ground it: retrieve sources and ask for citations.
- Allow abstention: make "I don't know" an acceptable, rewarded answer.
- Constrain it: schemas and enumerations for outputs, lower temperature for factual tasks.
- Verify afterwards: check claims against the sources with an automated verifier.
- Measure it: split answers into claims and report the share supported by sources, plus citation checks.
Sample answer
The model is trained to produce plausible continuations, not to verify facts, and it has no built-in signal for what it does not know. So it will produce fluent text even when the answer is not supported.
I reduce it in layers: ground answers in retrieved sources and ask for citations; allow and reward an "I don't know" path; constrain outputs with schemas or enumerations; lower temperature for factual tasks; and check claims afterwards against the sources with an automated verifier.
To measure it, I break each answer into individual claims and check each against the provided sources with an NLI model or an LLM judge, then report the share of supported claims. I pair that with citation checks: does the cited passage actually contain the claim?
Likely follow-ups
Common mistakes
- Saying hallucination is solved by a bigger model or a stricter prompt alone.
- Offering only one mitigation instead of layers (grounding, abstention, constraints, verification).
- Not explaining how you would measure faithfulness.
- Accepting citations without checking that the cited passage contains the claim.
- Penalizing "I don't know" so the system is pushed to guess.
The 0 to 1 AI Engineer Interview Playbook covers the answer frameworks, system-design walkthroughs and an 8-week plan.
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