Media was my proxy for who I could be. Now AI is everyone's proxy for everyone — and it learned our blind spots. Ten ways researchers can keep it honest.
Don't Frankenstein Your Flow: How to Integrate AI Into Research Workflows with Integrity & Intention
The Map Is Not the Terrain: What the AI-Native UXR Frontier Leaves Out
Jess Holbrook just published the clearest map of AI-native UX research I've read (Holbrook, 2026). If you lead a research team and you haven't read "Frontier UX Research Circa May 2026," go read it first, then come back.
He gets the big thing right: being AI-native is a systems problem, not a tools problem. Buying Dovetail or shipping one Claude project won't make you AI-native. You have to redesign how you work — how evidence flows from intake to insight, collection to synthesis to decision, so AI can participate at every step. I've been making the same argument to researchers and clients for a year, in nearly the same words: context engineering over prompting, systems over tools, amplification over automation. Human judgment and growth are the things you protect.
So this isn't a rebuttal. It's an extension. A "yes, and…" if you will.
AI Found 11 Usability Problems Humans "Missed." Problem is…10 Were Wrong.
The AI Disclosure Dilemma: How to Tell People You're Using AI (Without Freaking Them Out)
The AI Empowered Researcher: How to Dance with AI and Keep Your Soul
Many of us feel like using AI in our work is a "dance with the devil"—powerful, but unpredictable and a little scary. After years of trial and error, I've found the key isn't to follow, but to lead the dance. In this guide, I share my CRAFTe framework for writing better prompts and the ethical principles we need to keep our soul in the process.
Will AI Define Us? Three Possible Futures for UX Research
The future of UX Research with AI: utopian dream or dystopian nightmare? 😬👉🏻🤯
As posited on the panel with Sam Ladner, PhD, and Jared Forney at Dovetail’s Insight Out conference last month, Generative AI is forcing us to confront a critical question: Will we, as Researchers, create and define our collective future, or risk it being defined for us?
I've applied the "best/worst/base case" foresight framework to explore three potential paths forward for the Product & Design Research industry, from the "Ambling Along Status Quo" to the "Empowered Research Engine."
It's not about predicting, but preparing. Let's discuss our direction and how we can get there intentionally.
Dive into the article to explore these futures and share your thoughts! 👇🏻
🤖 The Rise of the Synthetic User: Gen AI's Impact on UX Research (and what it means for us)
Last month, I utilized generative AI to analyze 20 hours of interviews in just 14 hours (instead of over 80). The efficiency is mind-blowing... but at what cost and what opportunity? According to a recent HBR article, 77% of researchers are concerned about AI bias, and only 31% rating AI-generated data as "great," we're facing a critical inflection point in our field.
In the article, I note:
• 3 game-changing opportunities AI brings to UX research
• 3 serious challenges we can't ignore
• Thoughts on the impact and future of research
As researchers, what's our responsibility in this AI revolution?
What's your take: Will AI fundamentally enhance or erode the quality of UX research?
The bias of Chat.GPT and AI
So I did a little experiment with ChatGTP...name me 100 of the most influential BIPOC women in the past 100 years? It's answer highlighted the need to intentionally and consciously train AI with a diverse and representative dataset.
UR + CS = <3
UXR meet your BFF, Customer Success.
If there’s one piece of sage advice or golden rule that I might be able to offer you that will make your life easier (like buttah!) it’s this: customer success is your new best friend. Here are the 5 keys to engaging with CS and unlocking your client research meetings.