Interview Processes Evolve: Take‑Home AI Tasks Replace Whiteboard Tests

AI · 4 min read

Design hiring teams are redesigning their interviews to match day‑to‑day work: take‑home projects that mimic real briefs, incorporate live data, and require candidates to consider AI model outputs are becoming common. These tasks give candidates time to research, run simple generative experiments, and present thoughtful tradeoffs rather than perform under pressure in contrived exercises.

Interview panels have also added new evaluation criteria: how candidates document prompt experiments, how they assess model failure modes, and how they design for auditability and moderation. Recruiters find these signals more predictive of future success on AI‑enabled products than pixel‑perfect mockups completed onsite.

The new approach has downsides: longer take‑home projects require compensation to be equitable, and some firms struggle to standardize scoring across interviewers. To address these issues, hiring teams are providing structured rubrics, clear time expectations, and modest honoraria for multi‑day tasks.

For applicants, the practical tip is to treat take‑home AI tasks as portfolio pieces. Include a short appendix showing your prompt logs, evaluation criteria, and user testing plan. That transparency often separates strong candidates who can operate in hybrid design+AI environments from those who excel only at visual craft.