In my AI+UXR workshops, I recommend starting a fresh chat each time you ask the LLM to do a significant task. Why? Because UX research tools need to be reliable, and the more you talk to the LLM, the more that reliability takes a hit.
Read More
A highlight of last week’s AI+UXR workshop: seeing participants discover their own novel issues with AI synthesis for user research. This is the goal.
Read More
UX and design professionals are at a pivotal moment in the AI “revolution”: do we choose to define our value in terms of output or outcomes? Focusing on efficiency and deliverables (“output”) is the road to commoditization. But we still have an opportunity right now to shape the discussion about how to measure design impact.
Read More
As a design professional in 2025, what should you be doing to future-proof your career for AI? Last week I met with Bria Alexander, Brittany Hobbs, and Christopher Noessel to discuss the latest AI developments, and what was top of mind for them was not a specific new model or tool, but questions of access and resourcing.
Read More
Most AI+UX discourse today is framed in terms of adoption vs. rejection. In prep for Designing with AI 2025, I talked with Carla Diana, Kanene Ayo Holder, and Tom Armitage on why this framing does designers a disservice.
Read More
Designers use principles like unity, balance, and contrast to guide user attention in traditional interfaces, but what are the principles for designing "intelligent" interfaces? Josh Clark, Veronika Kindred, and Kritika Yadav may have cracked the code.
Read More
As design professionals struggle to figure out what AI means for the way we work, our partners across our organizations–PMs, engineers, and more–are all trying to answer the same questions. Erika Flowers and John Donmoyer show how designers are taking the lead in AI adoption, helping designers and non-designers alike to envision new ways of working.
Read More
What are the best explorations you’ve seen of AI as a design material? At Designing with AI 2025, we're highlighting two compelling case studies grounded in simple, hand-written math. Designers Lukas Moro and Aras Bilgen both kicked off explorations of generative AI with simple math problems, but ended up making very different discoveries about AI's possibilities.
Read More
We talk a lot about whether AI can replace traditional user research functions. But where is AI letting us explore user data in ways that are entirely new? That’s the question asked by Ian Johnson and Patrick Boehler, in two separate case studies from the very different lenses of data visualization and journalism.
Read More
In a recent interview about Designing with AI 2025, I discussed the top AI skills for UX professionals in 2025 and who to learn from.
Read More
In my AI + UXR workshop, I teach attendees to check the subprocessors of AI tools to understand what models they’re using under the hood. So it was delightful validation to see Simon Willison mention in a May 11 post that he’s started to do the same thing, and highlights the importance of sharing our learnings in public.
Read More
How are you evaluating your AI tools? This is the question UX and product leaders should be asking as they choose AI training and partnerships for their teams, which I recently discussed in an interview.
Read More
When you talk with UX practitioners about AI, one of their biggest concerns is "grift." They want to know where AI is actually useful and avoid buying into the hype of people who are only in it to make a sale. I talked about this in a recent interview.
Read More
I invited 31 researchers to test AI research synthesis by running the exact same prompt. They learned LLM analysis is overhyped, but evaluating it is something you can do yourself.
Read More
When we selected our speakers for Designing with AI 2025, we were looking for two things: creativity and critical thinking. And they have truly delivered.
Read More
It's easy to fall into the trap of confusing "output" with "impact." But as a researcher in a world of AI tools, that's a good way to devalue your work.
Read More
As more designers, PMs, founders, and researchers themselves begin to use generative AI tools for research synthesis, it has many researchers wondering whether it's good enough to replace their work. The short answer is it's a lot like using AI for anything else: AI output is "adequate."
Read More
AI is great at producing generic, average output. Average work may be perfectly fine to keep bringing home a paycheck, but if you don’t value it yourself, it will not be valued by others in the long term.
Read More