A polished portfolio no longer tells you how a designer works. AI tools now produce clean screens in minutes, so the work that matters is the judgement behind them. Figma's 2026 AI Report found designers doing development work rose from 21% to 41% in two years, and 60% of developers now do design work. The line between roles is moving, and your interview needs to keep up.
These questions come from how we assess designers at Design Strategists. Use them alongside a portfolio review, not in place of one.
1. Walk me through a recent project where you used AI. What did you use it for and what did you not use it for?
Listen for specific tools tied to specific steps, and a clear moment where they chose their own judgement over the output.
Watch for "I use AI for everything" or "I don't really use it." Both suggest they haven't worked out where it fits.
2. Describe something you built that was AI generated that you threw away.
Listen for reasons grounded in the user, the brand or the business, such as "it solved the wrong problem" or "it looked right but broke the flow."
Watch for reasons that are only about looks.
3. How do you check that an AI-assisted design is right before it gets implemented?
Listen for testing with real users, checking edge cases and accessibility, and reviewing with engineers early.
Watch for no checking step at all.
4. If you're designing a feature that uses AI, how do you help people trust it?
Listen for showing what the system is doing, letting people correct it, explaining confidence or sources, and designing for when it's wrong.
Watch for answers that treat the AI output as always correct.
5. How has your process changed in the last year?
Listen for concrete changes, such as prototyping in code, testing more variations, or spending more time on research because production is faster.
Watch for a process that sounds the same as three years ago.
6. Tell me about a time you worked directly in code or with a coding tool.
Listen for comfort reading or adjusting front-end code, or building working prototypes. This matters more as roles blur.
Watch for discomfort with any hands-on build work, if your team expects it.
7. How do you decide what's worth building?
Listen for starting from a user or business problem, using data, and saying no to ideas that don't earn their place. AI makes building easy, so this judgement is the job.
Watch for answers that start with the solution.
8. What AI tool or technique are you exploring right now, and what have you learned?
Listen for curiosity, a real experiment, and an honest view of its limits.
Watch for buzzwords with no example behind them.
How to score
For each answer, note whether the candidate showed judgement (knew when to use AI and when not to), evidence (gave a real example), and user focus (tied choices back to the people using the product). Strong candidates show all three on most questions.
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