A design exercise is a short design problem given during a UX hiring process. The candidate works through a prompt, such as "design a parking app for a busy downtown," live or at home.
It comes in 3 common formats: a live whiteboard challenge, a take-home assignment, or an app critique of an existing product. Interviewers typically evaluate how the candidate frames the problem, makes decisions, and explains tradeoffs.
Use cases
A badly run exercise wastes hours on both sides and tells the hiring team little.
Jumping to screens: A candidate starts sketching in minute 2, skips the user and goal, and can't explain why the design fits.
Spec work: A company asks for a redesign of its own checkout. The candidate spends 12 unpaid hours on work the company can potentially ship.
Take-home creep: The brief says "2 to 3 hours," but candidates who want the job spend 15. The process starts rewarding available free time rather than design ability.
How it's used in practice
Clarify first. Spend the first 5 to 10 minutes identifying the user, the main goal, constraints, and what's in scope.
Narrate decisions. Explain why you chose one idea over another and what you would test.
Sketch only the key flow. Draw the 2 or 3 screens needed to communicate the solution rather than polishing every detail.
Close with metrics. Name how you'd know the design worked, such as task completion or error rate.
For hiring teams: Use a fictional product, cap the time, share the evaluation criteria, and pay for take-homes that require substantial work.
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Pro-tip: Ask how the exercise will be evaluated before you start. It helps you spend your limited time on what matters.
Challenges & limitations
Pressure distorts performance: Live exercises can favor candidates who think well while speaking and disadvantage people who need more time to process ideas.
Artificial conditions: Candidates work without research or real-world data, so the exercise measures how they reason under constraints rather than how they would perform a complete product design process.
AI-assisted take-homes: Generated mockups make polished visual output easier to produce. Some teams add a live follow-up to evaluate whether the candidate can explain the decisions behind the work.
