If Product Managers can vibecode mockups and prototypes on their own, where does design fit into the future organization?

In a world where algorithms draft wireframes before you finish your coffee, designers face an existential choice: become strategic copilots or get automated into irrelevance. Few people see this crossroads more clearly than Nick Cawthon, a twenty-five-year design veteran, founder of research/design powerhouse Gauge (which I wrote about in last week’s issue as well), and the professor who teaches product teams to read data like narrative. In our latest Design Shift deep dive, Cawthon dismantles three myths: that design equals deliverables, that AI can replace user research, and that engineers and designers should live in separate silos. Here’s the fast, uncomfortable roadmap for keeping your craft indispensable in the AI decade.

In this issue/episode:

1. Design’s Value Lies in Direction, Not Deliverables

2. AI Can Scale Research…But Only When Anchored in Human Insight

3. Design and Engineering Are Merging—It’s Time to Build for Real

4. Want to go deeper? Nick offers various FREE tools to help designers, product people, and data analysts create more value.

Read on for my main takeaways from our conversation. 🎧 And…listen to the recording of our full conversation on the Design Shift podcast on Spotify and Apple and the Design Shift YouTube channel.

— Justin Lokitz

Design Deep Dive

AI Meets UX: The Nick’s Playbook for Future-Proof Design

First off, I am a huge fan of Nick Cawthon and what he does. Like many of the amazing design leaders I’ve interviewed (and had beers with) over the years, Nick is a designer’s designer. He doesn’t wait for instructions. He listens. He learns. He sketches. And he prototypes his way to the next steps.

I sat down for a burrito with Nick a few weeks ago and asked him how AI was affecting his design agency, Gauge. What he told me blew me away. Not only is he embracing AI, but…he’s using it to narrow the gap between the designs his clients are paying him for AND what the product/engineering teams actually want.

In this way, Nick is at once breaking the mold of what it means to be a “classically trained designer” while also doubling down on the value he creates and delivers to his clients…which is NOT just good design, but efficient, effective means to deliver said design to their customers.

Here are the three biggest takeaways from our conversation…

Insight 1: Design’s Value Lies in Direction, Not Deliverables

“It’s the facilitation in building up to that artifact to ensure that the direction and the velocity that we’re going in leads to success.”

“User experience was a refreshing notion… you were trying to understand what emotions were drawn from going through a workflow or a process.”

Nick reframes design not as a craft of outputs but as a discipline of decision-making and direction-setting. In his view, the artifact—whether it’s a screen, wireframe, or prototype—is just the byproduct. What matters most is the thinking that precedes it: the facilitation, the alignment, the emotional insight that ensures we’re solving the right problem in the right way.

He draws a sharp line between UI and UX. UI is what you see. UX is what you feel…and more importantly, how a system shapes your behavior and emotion. Usability is what you get once you actually test your UX with REAL CUSTOMERS in the wild. 

In an era where AI can generate layouts and developers can assemble interfaces with a few prompts, the designer’s job is no longer to pixel-push. It’s to orchestrate experiences with intention…and to test those experiences with real humans.

This means shifting from asset production to outcome facilitation. From styling to strategizing. From decorating screens to designing systems of meaning. Nick argues that designers should lean into behavioral science and human emotion…because those are the things machines can’t replicate.

In short: if your value as a designer is tied to the artifact, you’re already behind. The future of design leadership is upstream. It’s about guiding teams through ambiguity, aligning around what matters, and ensuring the velocity and direction of the work lead somewhere meaningful. The artifact is just the evidence of good strategy. Not the goal.

Insight 2: AI Can Scale Research…But Only When Anchored in Human Insight

“All that was predicated with these theories… coming from in-depth interviews with human beings.”

“You can’t go into 40 million reviews and just say, ‘let me pull some things out.’”

“That wouldn’t have been possible without strategy built from qualitative research.”

Nick issues a clear warning in the age of AI: data without context is meaningless. While large language models and automation can process millions of data points, they’re only useful when guided by informed human questions. Without that grounding, AI becomes a pattern recognition machine chasing ghosts.

In a project with Airbnb, Nick’s team analyzed 40 million reviews to understand why a specific product line underperformed. But they didn’t start with code. They started with conversations. It was only after conducting qualitative interviews and identifying clear hypotheses that the AI models were brought in to scale the analysis. The insight didn’t come from the algorithm. It came from people.

AI can accelerate the pace and scale of research, but it doesn’t know what to look for. That’s where human-centered strategy still reigns. Designers and researchers must continue to ask the right questions, listen deeply, and shape hypotheses rooted in real-world behavior. AI can then be used to validate, stress-test, and pattern-match across massive data sets.

Nick’s approach flips the dominant narrative. He’s not replacing human research with AI; he’s using AI to extend the reach of human empathy and judgment. It’s not about choosing between qualitative and quantitative. It’s about knowing when and how to combine them. The takeaway: human insight isn’t optional! It’s the foundation that gives AI any chance of producing meaningful outcomes.

Let AI do the heavy lifting, but let people set the direction.

Insight 3: Design and Engineering Are Merging—It’s Time to Build for Real

“Design operations are now writing rules for algorithms… that’s the shifting role.”

“Figma doesn’t feel like the web—it feels like an image map.”

“We’re trying to get as close as possible to a deliverable… developers are whose time we’re trying to save.”

“Everybody’s in the pool now. How do we find the definition of what design does?”

Nick argues that the wall between design and engineering has finally crumbled—and that’s a good thing (i.e., no more throwing Figma specs over the metaphorical wall to the engineering team). In this new era, designers are vibecoding fully functional prototypes, working in live component libraries, and partnering with engineers from the start. Tools like Cursor and AI-powered coding assistants aren’t just speeding up workflows. They’re collapsing the boundaries that used to define roles.

He’s blunt about the limitations of legacy tools like Figma. While they’ve been useful, they don’t behave like real products. They simulate screens, not systems. That gap creates costly rework downstream, especially in environments where time and engineering bandwidth are limited. His team now delivers production-ready interfaces built directly in code, because that’s what product teams actually need.

This evolution demands new skills. Designers must be comfortable shaping prompts, building within constraints, and understanding how their choices affect implementation. Likewise, engineers must be open to collaboration and iteration, not just execution. In Nick’s view, the most valuable players are those who operate at the seams: hybrids who understand both intent and implementation.

The bigger shift is cultural. Nick calls it out directly: “Everybody’s in the pool now.” There’s no more tossing files over the fence. The future of product design is collaborative, technical, and outcomes-driven. The job isn’t just to design something beautiful. It’s to build something real, fast, and right. The teams that thrive in this environment won’t be the most specialized. They’ll be the most integrated.

Justin’s Notes

What can I say after a conversation like that?!

As I mentioned above, I was gobsmacked (great word BTW) by Nick’s ability to see AI and design tools for what they are…materials for value creation. In this new paradigm, it’s incumbent on designers, product people, engineers, and everyone in between to employ these amazing (and sometimes scary) new materials for good.

This is about blending AI with HI (human intelligence), and…using that magic blend to do things that we could not do before. It’s also about claiming our own agency in how we collaborate and co-create in the future. In this future, we decide how work gets done, who does that work, and most importantly, how we want humans to feel about it all. I think that’s the coolest part.

Want more? Connect with Nick and tell him Justin sent you!

Resources

• Curated self-assessments for UX & Design Teams at retrain.gauge.io

• https://gauge.io/

• https://cursor.com/en

Subscribe to Design Shift for more conversations that help creative professionals grow into strategic leaders.

Want to go deeper?

If it wasn’t already clear, Nick is all about value creation and delivery. As part of this, he has created some incredible FREE resources to help designers, data analysts, and product people understand and extract meaning from their data.

Check out AnchorBox, a segmentation and clustering engine, which employs an evidence-based approach to both segment data and help uncover the unique factors for each segment.

Visualization Sandbox, another free resource created by Nick, is built to enable researchers to see and compare unstructured datasets through three open-source visualization displays.