AI Engineering · LLM applications that ship
When should a human stay in the loop?
Short answer
Keep a human in the loop when actions are irreversible, high-value or regulated, or when confidence is low. Automate the reversible, low-risk steps and escalate the rest.
Human review is not a binary choice for the whole product. The right pattern is tiered: the model drafts and the human approves, or the model acts automatically below a risk threshold and escalates above it. The design question is what happens when the model is wrong.
- Require approval for payments, deletions, external messages and permission changes.
- Escalate when retrieval confidence is low or the request is out of scope.
- Show the evidence and the proposed action, not just a yes/no button.
- Measure how often reviewers override the model, and feed those cases back into evals.
Follow-ups you should expect
Interviewers use these to check whether the first answer was understanding or memorisation.
- 1How would you set the confidence threshold for auto-approval?
- 2What should the reviewer see to make a good decision quickly?
- 3How do you avoid alert fatigue in a review queue?
Say it in the interview
I keep a human in the loop where a mistake is expensive or hard to undo: money movement, deletions, external communication, regulated decisions. For low-risk reversible actions the model can proceed and we audit afterwards. The reviewer needs the evidence and the proposed action, not just a confirm button. I also track override rates, because if people approve everything the control is theatre rather than safety.
Use this as a model, not a script. Saying it in your own words is what makes it survive follow-up pressure.
Related questions
Reading is step one
Now say it out loud.
Understanding an answer and delivering it under pressure are different skills. Rehearse this topic in a live AI Engineering mock interview and get scored feedback on depth, clarity and confidence.