The AI Product Designer's Interview Guide

A complete AI product design interview system — 540 pages that take you from diagnosis to offer

Your work is good and it is no longer converting. That is not a talent problem, it is a market that repriced what you were paid for. This guide explains exactly what changed, then rebuilds your practice around what still counts

What's inside:

Nine parts covering the full journey, from understanding why the ground moved to negotiating the offer:

The Shift: How every tool generation absorbed the previous job, why a Figma-only portfolio now reads as under-levelled, and the eleven challenges you are actually facing

The Market: How big tech levels you on scope, ambiguity and influence, how to read a job post structurally, and what every interview round is really measuring

What You Already Have: Turning Figma depth into tokens, component architecture and constraint-based layout — plus problem framing and how to describe your week credibly

Understanding AI: Only the model behaviour that changes an interface. Non-determinism, latency, confident wrongness, evaluation, and a failure taxonomy you can reason from

Working in an AI Team: Collaborating with ML engineers, the metrics that actually work when adoption misleads, and ethics treated as design decisions rather than principles

From Figma to Code: Tokens to CSS, semantic HTML, building with AI assistants and everything they get wrong, Git and GitHub, and the handoff developers actually want

Prototyping and Performing: Demonstrating non-deterministic features honestly, the live tool round, and the design challenge and take-home with three fully worked examples

Telling the Story: Case studies rebuilt around decisions rather than process, ten behavioural stories mapped to what rubrics assess, and a resume that survives both a parser and forty seconds

Landing It: Levelling and compensation, the first ninety days, and how to stay current so this does not happen to you again

Built around one thing you make. Across the nine parts you specify, design, build, ship and evaluate a small real product. You finish with a live URL, a repository, an evaluation set and stories that answer what interviewers are actually assembling evidence for.

Who this is for:

UX and product designers with real craft who are finding the market harder than their ability suggests it should be.

Especially valuable for UX designers moving into AI-driven product work — where the usual research, flows and usability toolkit still matters but is no longer sufficient, and where nobody has explained what the additional layer actually is.

Also for those with strong work behind a client login or an NDA, and nothing recent they can show.

If you are tired of a beautiful portfolio that stops converting at the second round, this is the structured answer. It teaches you to frame problems rather than receive them, to design for output you cannot predict, to hand engineering working code rather than a file, and to describe your work at the level you actually operated at.

Not a promises-based course. A working system, with an object at the end of it.