Lessons from product work: prototyping, user research, prioritization, stakeholder communication, and shipping.
An AI issue summary can sound convincing while overstating the evidence. Here are the checks I built in for affected users, overlapping sources, missing information, and uncertain conclusions.
Written requirements asked users to picture the finished tool. Familiar, clickable prototypes helped them give more specific feedback while we still had room to change the design.
Our product reviews didn’t require elaborate pre-reads, but I kept making them. Building a different preparation workflow helped me question what I actually needed to bring to the conversation.
I thought adapting my release notes skill meant changing its sources. Then I discovered how much of the workflow assumed I already knew who would read the result.
Practical tips from Rachel Fairbanks’s Product School session on preparing user tests, asking questions without influencing answers, and turning feedback into priorities.