When we’re thinking about where to take our product next, we actually take a lot of inspiration from our customers and the Figma Community, to see how they’re stretching our product in interesting or unexpected ways. We saw this happening in the early days of the pandemic. Our users were starting to use Figma for everything from brainstorming ideas to running team warm-up activities, to even putting on social events for people to get to know each other. We saw a lot of use cases that got us thinking.
The boundary between engineering, design, and product management is blurring. Some of us used to have a mental model in which roles and responsibilities dictated how things work—that designers do one thing and engineers do another, for example. Increasingly, more people are crossing team lines to problem solve together...Now, it’s not about who “owns” what—it’s more of a collective endeavor. And the roles have become more interlocked, and I think that’s fundamentally a good thing.
Design is non-linear. At Figma, we often talk about “embracing the mess,” and that really means leaning into the chaos and complexity that makes the design process what it is. Even once you have the seedling of an idea, you need to explore and iterate, then pull back and evaluate to see what’s working and what’s not. Sometimes you’ll scrap an idea after a brainstorm session, and other times you’ll get pretty far with a concept, but still need different perspectives and input to move forward.
Since we launched FigJam back in April, teams having been using it to grow all kinds of ideas into great designs. We recently caught up with Figma's VP of Product, Yuhki Yamashita, to hear what it was like to build FigJam and how things have changed since then. Here, he reflects on the evolving role of design and product management, what it means to welcome “non-designers” into the process, and the future of FigJam.
There is increasing concern that most current published research findings are false. The probability that a research claim is true may depend on study power and bias, the number of other studies on the same question, and, importantly, the ratio of true to no relationships among the relationships probed in each scientific field. In this framework, a research finding is less likely to be true when the studies conducted in a field are smaller; when effect sizes are smaller; when there is a greater number and lesser preselection of tested relationships; where there is greater flexibility in designs, definitions, outcomes, and analytical modes; when there is greater financial and other interest and prejudice; and when more teams are involved in a scientific field in chase of statistical significance.