The field moves weekly. How do you decide whether a new AI technique or model is worth adopting (hype vs substance)?
Chasing every new model is as harmful as ignoring them all. Interviewers want a repeatable filter for signal versus hype, plus the discipline to test on your own problem. Here is that filter.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
Chasing every new model is as harmful as ignoring them all. Interviewers want a repeatable filter for signal versus hype, plus the discipline to test on your own problem. Here is that filter.
Lead with where the obvious approach breaks, because that is the judgment they are screening for — most candidates jump straight to the happy path and lose the room.
Then walk the failure back through the pipeline in order, naming the one metric the customer's exec sponsor actually cares about before you propose the fix.
