Most research teams think they're adopting AI. In reality, they're Frankensteining their flows—quietly ruining their ROI, their reputation, and their research integrity. And it all comes due as mounting risk the moment regulation catches up.
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.
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.
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.
