Kent talks with Will King about bringing an industrial design mindset into software: human factors, observing real users, and why good product engineering starts with caring enough to notice what frustrates people.
They dig into product debt, support as a product superpower, pruning features without breaking trust, and how to use AI agents for exploration and critique instead of only faster implementation.
Will's path runs from designing bucket trucks to self-taught software engineering, education products, and database tooling, and that background gives this episode a distinctive lens: software is still a product people use with bodies, habits, emotions, and mental models. The conversation makes product sense concrete through examples like onboarding timing, course complexity, support workflows, and the small confidence signals that separate stable-feeling products from merely functional ones.
You'll hear why watching users work keeps surfacing across this series, how to tell broken experiences from merely unpopular ones, why user feedback usually improves polish more than strategy, and how product engineers can stay valuable in an agent-heavy future by understanding both the user and the constraints of the software medium.
Homework
- Use AI agents more for gathering than executing: explore multiple solution paths, adjacent domains, and missing context before you ship.
- Give agents richer context like user demographics, constraints, and likely mental models, then use your own judgment to evaluate what comes back.
- Slow down long enough to question assumptions before implementation; use AI as a creativity and critique tool, not just a code accelerator.
Resources
Guest: Will King
Host: Kent C. Dodds
Video
