Why insist on a baseline, and what counts as one?
Answer it out loud before you open anything. The value of the flags below is in comparing them to what you actually said — including whether you asked about the data before naming a model.
The production scenario behind the question
A support team wants a model to predict ticket resolution time so they can set customer expectations. A contractor delivered a gradient-boosted model with a validation MAE of 6.1 hours (illustrative) and a slide saying "state of the art". Nobody knows what the MAE of "the median for this ticket category" would be.
What it is really testing
Whether the candidate treats a metric as meaningless without a reference point, and can name a ladder of baselines from trivial to strong. The best candidates also know that the baseline is sometimes the deliverable.