Last week in the Rosenverse, we hosted a session in which Dolly Parikh as a part of our Exit Interviews series. In it, Dolly discussed her transition from UX and product to social and environmental causes, and how others can make a similar change in their careers.
Log into the Rosenverse to watch the recording.
See what you missed below.
May 21: Dolly Parikh reflects on her transition from a long career in UX, Product, and Information Architecture to her current work as an Impact Strategist and Social Entrepreneur advancing sustainable development. She shares how Human?Centered Design, Systems Thinking, and Innovation Practices became the foundation for her shift into Ecosystem Conservation at The Nature Conservancy and her mentorship of Global Social Ventures. This session offers UX practitioners an inside look at how design skills translate beyond the tech industry and how they can be leveraged to drive regenerative, systems?level impact in the social and environmental sector. Watch the recording »
As a social entrepreneur, Dolly Parikh focuses on impact, strategy, and innovation capacity building for sustainable development. At The Nature Conservancy, whose mission is to protect land, water, and ocean on which life thrives, she leverages Human-Centered Design, Systems Thinking, and Innovation methodologies to drive impact in ecosystem conservation. After spending a couple of decades as a Product, UX, and Information Architect in B2B and B2C Technology Companies, Dolly expanded her design and problem-solving practice for social good. Read more »
This Q&A was drawn from the Rosenverse Live session.
A: UX is fundamentally about understanding people, clarifying complex problems, and designing better experiences. Those same skills are powerful in the impact sector because they help teams communicate clearly, prioritize effectively, and build services that are easier for people to use.
A: The biggest leverage comes from communication and storytelling. When you can frame a problem well and show why it matters, you make it easier for others to align around the solution and move the work forward.
A: AI can help close resource gaps when teams are underfunded, understaffed, or stretched thin. Used thoughtfully, it can support faster operations, better knowledge access, and more scalable service delivery.
A: Research, facilitation, synthesis, and design strategy are useful almost anywhere people need better decisions and better services. Those skills travel well because they are built around understanding behavior and improving human systems.
A: AI should support people, not replace judgment. In the impact sector, it can help stretch limited resources, but it works best when teams stay focused on equity, context, and the actual needs of communities.
Catch up on last week’s recordings, and mark your calendar for upcoming events.
See you in the Rosenverse!
Get acquainted with AI or get left behind.
That seems to be the consensus these days across all industries. As artificial intelligence (AI) continues to boom, we want to explore how the technology is impacting the user experience (UX) space. According to Maze’s 2026 Future of User Research report, two out of three researchers are using AI at some point in their process. With such a significant number, it’s crucial to stay up-to-date on the latest and greatest in artificial intelligence.
But how can researchers keep up when everything seems to be moving at the speed of light?
Have no fear; we’ve compiled some of the top resources available to you in the Rosenverse to help keep up with AI trends in user research. So now you don’t have to worry about getting left behind. View all the resources in this post here.
Since the first whispers of ChatGPT came onto the scene, we at Rosenfeld have kept an ear to the ground for how artificial intelligence has been reshaping the research experience.
In 2023, we hosted a panel moderated by Dr. Jamika D. Burge, How UX researchers can partner with (and not be replaced by) AI, in which panelists spoke to their own lived experiences and expanded on the most crucial actions researchers could take at this turning point in UX. Alexandra Jayeun Lee of Microsoft said that “learning prompt engineering will make us better researchers in the same way coding helped designers.”
Since the beginnings of the AI boom, companies everywhere have been seeking out ways to incorporate the newest technology—much to the behest of some employees. How can we implement AI into our work without it replacing us? Will AI take away jobs like predicted when it first exploded? (Spoiler: Not really). When it comes to user research, innovation involves utilizing AI in a way that is a research partner, rather than a shortcut or a replacement.
“Learning prompt engineering will make us better researchers in the same way coding helped designers.”
– Alexandra Jayeun Lee
When used as a tool, AI has the potential to do lots of heavy lifting and ease burdens of things such as transcription, pattern mapping, data organization, and more. There are many tools out there that additionally boast of insight generation, but it’s important to pair these tools with a human perspective, keeping an eye out for confirmation bias and feedback loops in AI-generated information.
By crafting the right prompts and using AI to its strengths, user researchers can develop a companion in their research, and a helpful, trainable one at that.
Watch: How UX researchers can partner with (and not be replaced by) AI
While artificial intelligence can make researchers’ lives easier, it has its limitations.
In Research That Scales, author Kate Towsey says to “Treat AI as you would any other tool: question where it will be best used, and how it will impact the culture, results, and value of research.”
Jake Burghardt, author of Stop Wasting Research, has dedicated a whole book to building research repositories and limiting research waste—even without the help of AI. Yet Jake advocates for appropriate AI use, citing the time it can save, as well as the support it can offer. At the same time, he cautions that there is no “push-button” technology that will magically solve the problem of research waste.
“When appropriate, adding AI-based features to research tooling can valuably support operations…AI in defined use cases can be a complement for researchers’ smarts, sometimes saving extensive manual efforts.”
– Jake Burghardt
This is a situation in which understanding AI’s benefits versus its limitations is critical. Artificial intelligence can be of great use to the user research process. In fact, User Interviews’ 2024 AI in UX Research report cites that 48% of surveyed participants cite AI’s speed as a benefit. And in Maze’s 2026 User Research Report, 63% cite improved turnaround time as a benefit. The evidence here is clear: AI can be a timesaver for UX research. But it’s not the answer to everything.
Build Better Products author Laura Klein presented her talk, Human vs. machine: Testing AI’s ability to synthesize and analyze research at Advancing Research 2026 this past March, as a way to demonstrate this exact conundrum. Here’s a peek at some of her findings:
Read: Research That Scales by Kate Towsey
Read: Stop Wasting Research by Jake Burghardt
Watch: Human vs. machine: Testing AI’s ability to synthesize and analyze research
What better way to keep up with trends than by hearing from the researchers on the front lines of this innovation?
There are many resources out there for user experience professionals, but the Rosenverse combines thousands of hours of conference and community videoconferences with years of podcast episodes, dozens of high-quality books, and a UX-specific chatbot. We may be biased, but we seriously cannot recommend it enough. Here’s our two favorite ways to stay up-to-date on AI trends:
Did you know that Rosenfeld Media hosts free virtual events—around 100 per year?
We like the keep our finger on the pulse of all things UX, and right now that includes frank discussions about AI. Here are some of our recent Rosenverse Live sessions about artificial intelligence:
The Designing with AI conference is entering its third year as a standout in the UX space. Since 2023, Rosenfeld Media has been painstakingly crafting the annual event with the most poignant and relevant case studies and talks about AI.
Who better to learn about AI from than the designers and researchers on the ground using it?
If you’re Rosenverse Gold member, you can watch all past Designing with AI conference sessions. But you don’t have to miss out: Designing with AI 2026 is in just a few short weeks! Register now for #DwAI2026.
Watch: The Handoff is Dead: Design-Led Engineering with AI Agents
Watch: When AI Agents Meet Reality. Service Design Lessons from a Pilot
Watch: Improving Democratized Research with CustomGPTs and Gems
Attend: Designing with AI 2026
How are you staying up to date with the latest AI trends in user research? Do you believe AI is the next evolution of research, or do you have a more cynical take? Let us know!
You can access all resources listed in this post here »
AI may be built on language—but according to Paul Ford, we’re still struggling to find the right words to describe what it’s actually doing to our work and thinking. Lou and Paul explore how language shapes our ability to understand—and responsibly use—AI.
Drawing on his dual background in programming and writing, Paul shares a set of evolving “rules” for working with AI: don’t let it replace your thinking, be wary of its tendency to flatter, and build systems that help you verify and structure its output rather than blindly trusting it. He explains how he uses AI to accelerate prototyping and research while still preserving human judgment, creativity, and accountability.
The discussion also zooms out to the broader cultural moment. From skeptical college students to industry hype cycles, Paul argues that people are more discerning than we often assume—and that AI’s impact will play out in diverse, deeply human ways.
Paul will be the opening speaker at the upcoming Designing with AI conference, where he’ll expand on these ideas and introduce new language for navigating this rapidly evolving space.
His takeaway? We’re not at the end of history—we’re in a messy, fascinating transition, and the best we can do is stay curious, thoughtful, and engaged.
This Q&A is drawn from the podcast episode.
A: The image I keep coming back to is the difference between jagged and smooth. AI output tends toward smooth — it’s confident, fluent, well-structured, and immediately plausible. That smoothness is actually a kind of trap, because the jagged stuff — the weird hesitation, the half-formed idea, the counterintuitive hunch — is often where real thinking lives. Your own roughness isn’t a bug to be edited out. It’s evidence that something is actually happening upstairs.
When you outsource too much of your thinking to AI, you get smooth output but you risk losing the texture of your own mind. The goal isn’t to resist AI — it’s to stay jagged enough that you’re still genuinely contributing, still thinking your own thoughts, rather than just editing what a model handed you.
A: Because the words we use to describe what AI is doing shape whether we can think clearly about it at all. Right now, the available language is mostly borrowed — from science fiction, from corporate marketing, from hype cycles. We say models “hallucinate,” we say they “understand,” we say they’re “thinking.” None of those words are quite right, and using them imprecisely leads to both overconfidence and misplaced fear.
Part of what I want to do — and what I’ll be expanding on at the Designing with AI conference — is develop better, more honest vocabulary for what these systems actually do and don’t do. You can’t navigate something responsibly if you don’t have language that lets you describe it accurately. That’s not a philosophical nicety. It has real consequences for how teams use these tools and what decisions they make.
A: I want to be careful not to oversell these as rules, because I keep revising them — which is part of the point. The first is the most important: don’t let it replace your thinking. Use it to accelerate your thinking, to stress-test your ideas, to cover research ground faster. But the judgment, the synthesis, the thing you’re actually trying to figure out — that has to stay with you. The moment you hand that over, you’ve also handed over the accountability.
The second is to be genuinely wary of the flattery. These systems are natively inclined to tell you that your idea is good. They are almost constitutionally agreeable. If you’re a leader, that is an extremely dangerous quality to expose yourself to — you will hear a lot of “yes, and” when what you actually need is “wait, but.”
The third is to build systems around the output rather than trusting it directly. Verification structures, review layers, prompts that force the model to argue against its own previous answer. You want to narrow the risk before you let it run.
A: When it gets into that weird social relationship where it’s telling you that was a good idea, that’s where my alarm bells go off. The native buttering-up quality of these technologies is genuinely dangerous, because of course you always want to hear it — especially when you’re a boss.
People in positions of authority are already somewhat insulated from honest feedback. Direct reports learn quickly what the boss likes to hear. And now you have a technology that has essentially been trained to be agreeable, to be helpful, to give you what you seem to want. That’s not a neutral tool. It can quietly reinforce your blind spots and confirm your assumptions without you ever noticing it’s happening.
The antidote is to be deliberate about using AI to challenge you, not just assist you. Ask it to find the flaws in your plan. Ask it to steelman the opposing view. Ask it to tell you what you’re probably missing. That takes discipline, but it’s the difference between AI as a thinking partner and AI as an expensive yes-man.
A: The key move for me is front-loading the structure. Before I let a model generate anything significant, I put real effort into defining the constraints — what I’m trying to learn, what format I want, what I already believe, and crucially, what I want to verify independently afterward. You can really narrow your risk when you’re working with this stuff, and then you can let it go and see what it comes up with.
For prototyping, AI is extraordinary. You can go from an idea to something you can actually interact with and react to in a fraction of the time it used to take. That changes the creative and strategic process in ways that are genuinely exciting. But I’m always conscious that a prototype that looks polished isn’t the same as an idea that’s been validated. The speed is real; the judgment still has to come from somewhere else.
For research, I use it to cover ground quickly and surface things I didn’t know to look for — and then I go verify the things that matter. The model is a collaborator, not an oracle.
Paul Ford is a multidisciplinary technology founder, writer, and product leader based in New York with 16+ years of experience building software-driven companies. He co-founded Aboard and Postlight, where he built a design-driven product studio and helped Postlight grow into a 100-person firm before its acquisition by NTT Data in 2022, then returned to focus on new product initiatives and climate-data storytelling. As a prolific writer and editor, he has contributed to WIRED, Harper’s, NPR, The Morning News, and New York Magazine, blending technical rigor with cultural insight. His ventures range from solo projects like Ftrain.com to community experiments like tilde.club, reflecting an enduring passion for hands-on creation and open communities. Read more »
0:11 – Meet Paul
5:30 – Can language keep up with technological change?
12:48 – Paul’s rules for professionals
18:11 – Where is the slippery slope? Paul weighs in.
22:23 – Paul reveals his gift for the audience
23:03 – 5 reasons to use the Rosenverse
25:18 – A story about some NY college students
29:21 – The anger and skepticism toward AI
35:18 – Wrapping up
Do your designs adapt to users in the moment? Are you using artificial intelligence to its full potential in your products?
Sentient Design: Crafting Intelligent Interfaces with AI is the book for you.
In fact, Kirkus Reviews just called it “An essential guide for building responsible and revolutionary AI-mediated user experiences.”
With this book, you’ll learn to create experiences that crackle with awareness and agency, adapting to your users in the moment. Sentient Design is the practice of crafting intelligent interfaces: dashboards that design themselves, apps that manifest on demand, agents that just get it done, and much more. This groundbreaking read by Josh Clark and Veronika Kindred gives designers and product leaders the practical framework and imaginative perspective to deliver extraordinary new products using AI as a design material.
If you’re a…
…This book helps you decide what to make and why it matters, giving you the patterns and process to conjure the next generation of AI-powered products.
Don’t just take our word for it—see what the professionals have to say!
“Josh and Veronika have done something so rare. They’ve named a thing that was already happening, but we didn’t have language for. Sentient Design is a smart, generous exploration of how we’ll engage with AI as humans and as designers. Essential reading for anyone building the next generation of digital experiences.”
—Katja Forbes, CX futurist and author, Machine Customers: The Evolution Has Begun
“Sentient Design is the ultimate guidebook to a world where the best interface is a thinking one.”
—Golden Krishna, author of The Best Interface Is No Interface: The Simple Path to Brilliant Technology
“Sentient Design offers clear vocabulary and concrete examples to help designers better imagine what’s possible with machine intelligence as design material.”
—Randy Hunt, head of design, Notion
AI design is the broader practice of designing products that use artificial intelligence. Sentient design is more specific: it focuses on interfaces that feel context-aware, adaptive, and behaviorally responsive to the user.
It changes how UX teams think about flows, states, feedback, and trust. Instead of designing only what users click, teams also design how systems should respond, explain themselves, and adjust in real time.
Designers need systems thinking, content strategy, interaction design, research skills, and a strong understanding of AI limitations. They also need to design for uncertainty, not just ideal user journeys.
The biggest challenges are unpredictability, transparency, user control, and trust. When interfaces adapt dynamically, designers must make sure the experience still feels understandable and safe.
Last week in the Rosenverse, we hosted a session in which Nathan Shedroff, Hugh Dubberly, and Thomas J. McLeish explored what might replace the design school as we know it, and who gets to define what education means in the future.
Log into the Rosenverse to watch the recording.
See what you missed below.
May 8: Design schools are collapsing—literally. When institutions like California College of the Arts close after more than a century, it’s clear our old model of design education can’t survive economic pressure, tech disruption, or outdated ideas about what “training” should be. So what comes next? Nathan Shedroff, Thomas J. McLeish, and Hugh Dubberly will lead an exploration of what might replace the design school as we know it: apprenticeships, corporate academies, AI mentors, decentralized credentialing—and models no one’s tried (yet). It’s not just about how designers will learn, but who gets to define what education means in the future. Watch the recording »
Nathan Shedroff is the executive director of Seed Vault Ltd, a Singapore-based platform building an independent, trusted bot economy on the blockchain. He manages a cadre of experienced bot enthusiasts and technologists developing new ways to ensure user privacy, shepherd the shift to this new paradigm, create ways for people to profit from their creative work, and save the business sector from its most critical threat ever. He is a design pioneer turned entrepreneur and an international educator, speaker, and consultant. Read more »
Hugh Dubberly was a Creative Director at Apple Computer (1986 – 1994), managing graphic design and corporate identity; he also produced the technology-forecast film “Knowledge Navigator” presaging the Internet and interaction via mobile devices. At Netscape (1995 – 2000), he was Vice President of Design managing groups responsible for the design, engineering, and production of Netscape’s web services. He co-founded Dubberly Design Office (2000), a software, system, and service design consultancy, whose clients have included Amazon, Cisco, Facebook, Google, IBM, J&J, Lilly, Nikon, Samsung, and Visa. Read more »
Thomas J. McLeish is a Lecturer in the Master of Design program at UC Berkeley and at California College of the Arts, where he teaches graduate courses in AI prototyping and emerging design practices. At UC Berkeley, he serves on the Jacobs Institute Executive Committee’s AI working group, shaping how the Institute integrates AI across its design programs. An MIT Media Lab alumnus, he was shaped by Nicholas Negroponte’s vision of responsive, conversational systems and by Gordon Pask’s cybernetic idea that intelligent systems should engage users in dialogue rather than deliver static responses. His reconstruction of Pask’s Colloquy of Mobiles—exhibited at the Centre Pompidou and now in the permanent collection at ZKM—extends that lineage into contemporary practice. Read more »
This Q&A was drawn from the Rosenverse Live session.
A: Design education is being pressured by changes in technology, work, and knowledge sharing. As communication tools evolve and AI reshapes how people learn and collaborate, the old classroom model may no longer be enough on its own.
A: Possible replacements include apprenticeships, corporate academies, decentralized credentialing, and hybrid systems that combine making, theory, and mentorship. The larger point is that design education may become more distributed and less tied to a single institution.
A: AI could act as a mentor, a collaborator, and a tool for personalized learning. But it also raises bigger questions about who teaches, who evaluates, and how knowledge gets validated when technology can generate answers quickly.
A: Critical thinking remains essential, but it works best when paired with critical making. In design, thinking and making reinforce one another, so learning should move back and forth in a recursive loop rather than separating theory from practice.
A: That is one of the most important questions. If education moves beyond schools, then employers, communities, platforms, and AI systems may all influence what counts as legitimate learning.
Catch up on last week’s recordings, and mark your calendar for upcoming events.
See you in the Rosenverse!
Designers, how have you been incorporating artificial intelligence (AI) into your practice?
Whether you’re embracing the innovative technology with open arms or eyeing it with a healthy dose of skepticism, one thing is certain: the future of design is changing. Fast.
But what does designing with AI look like? And what are the benefits, downsides, implications, and impact of using this tool?
Don’t fret—the Designing with AI conference is here to help.
Designing with AI is a live online conference hosted by longtime UX book publisher and conference host Rosenfeld Media. Across two days, experts and renowned speakers in the user experience and design worlds come together to present case studies, panels, and talks about how they’re incorporating AI into their work, as well as their hopes, fears, and predictions for the future of the industry. Designing with AI 2026 is the third rendition of the event.
The program, crafted by our curation team led by Llewyn Paine, is made up of a unique blend of case studies, panels, and featured talks from over a dozen experts spanning two days.
Our expert speakers hail from companies such as Dalberg Design, JP Morgan Chase, and Cloudflare. For a full speaker list, click here.
Now, let’s explore the talks that we’ve just added to the program!
Tuesday, June 9, 2026 | 1:15pm – 1:45pm PT
Vibe coding can feel empowering for designers, but production code plays by different rules–and designers can’t see the full picture. In this panel, our panel members will unpack the hidden constraints, tradeoffs, and expectations that shape real codebases. Learn what engineers wish designers understood about AI?generated code, and how to collaborate more effectively as design and engineering roles continue to blur. View talk info »
Changying (Z) Zheng leads Product Experience Operations at Cloudflare, a global internet infrastructure and security company. She’s passionate about improving the lives of those she works with daily. Prior to this position, Z led design teams in-house and at design consultancy firms. Z has also a background in EdTech and spent her time teaching and mentoring the next generation of designers.
David Eisner is a Product Design executive with over 25 years of experience bridging the gap between design and engineering. Currently the VP of Product Design and Research at Amwell Healthcare, he pioneered a hands-on AI training program that empowers designers to ship production-ready frontend code. This approach eliminates traditional handoffs and miscommunications while raising the bar for product quality. Previously, David held senior leadership roles at Amazon, Audible, Haven, Plated, and Huge Inc. He is also the founder of CraftAmplify (craftamplify.com), where he actively teaches designers how to use AI to gain independence and creative agency. David holds a B.S. in Interactive Media from Carnegie Mellon University and an M.A. in Media Design from Keio University in Japan. A lifelong builder and explorer, he spends his time off the clock experimenting with emerging tech, navigating the NYC food scene, and planning his next travel adventure.
Elyse Holladay (she/her) is a long-time design systems practitioner and speaker, currently the Staff Design Engineer for Color Health’s Continuum Design System. She was tapped to start the first design system team for Indeed, has taught hundreds of hours of technical training content, and has been invited to speak at well-known industry events such as Clarity, CSSConf Berlin, and Frontend Design Conference. She is also the host of On Theme: Design Systems in Depth. She’s a technical generalist, off-the-charts extrovert, avid reader, and expat Texan with an armadillo tattoo.
Amelia Wattenberger is a developer, designer, and prototyper. She spent almost a decade building data-intensive dashboards, and the last half-decade exploring ways to innovate on how developers work. Currently, she’s supporting companies at Sutter Hill Ventures.
Tuesday, June 9, 2026 | 2:30pm – 3:00pm PT
Create experiences that have the awareness and agency to adapt to users in the moment. Sentient Design is the practice of crafting intelligent interfaces: dashboards that design themselves, apps that manifest on demand, agents that just get it done, and much more.
Learn how AI can elevate design (and designers!) instead of replacing them by grinding out efficiencies. Instead of treating AI as a tool, Sentient Design invites you to use AI as a design material, woven into the interface itself. What entirely new kinds of experiences can we create? What dramatic new value can they deliver?
Intelligent interfaces are the new frontier of experience design. This session delivers a map of the territory, as well as the framework and perspective to deliver these experiences in your own practice. View talk info »
Josh Clark is principal of Big Medium, a digital agency that helps complex organizations design for what’s next. Josh has over 30 years of experience in emerging technology, user experience, and design innovation. His projects include future-friendly interfaces for AI, connected devices, and websites for many of the world’s biggest companies.
Josh is co-author with Veronika Kindred of the book Sentient Design: Crafting Intelligent Interfaces with AI (Rosenfeld Media, 2026). Josh coined the phrase Sentient Design in 2024 to describe the practice of crafting digital experiences with awareness and agency that adapt to your users in the moment.
Veronika Kindred is a designer and researcher at digital agency Big Medium, where she defines and solves design problems alongside some of the world’s biggest companies. She travels internationally to lead Sentient Design workshops and speak to teams at startups and Fortune 100 companies alike.
Veronika is co-author with Josh Clark of the book Sentient Design: Crafting Intelligent Interfaces with AI (Rosenfeld Media, 2026). Sentient Design describes the practice of creating digital experiences that crackle with awareness and agency, adapting to your users in the moment. These are intelligent interfaces: dashboards that design themselves, apps that manifest on demand, agents that just get it done, and much more.
Josh and Veronika’s upcoming book, Sentient Design: Crafting Intelligent Interfaces with AI releases on Tuesday, June 9—the first day of the Designing with AI conference!
Pre-order the book now at 15% off to receive a complimentary ebook with your purchase—delivered straight to your downloads upon release!
The dramatic rise of OpenClaw hints at a future where AI doesn’t just generate text: it owns tasks. In this panel, hear how designers are inventing new ways of working with AI agents, from AI “chiefs of staff” to their very own production crew. Together they’ll speculate what the agent shift signals for designers today, and how we can prepare for a more agentic future. View talk info »
Christian Crumlish is Director of Product at Kind Systems, helping governments develop transformative digital services. Author of Product Management for UX People and curator of the Design in Product conference, he brings a unique perspective from leading product at California’s Office of Digital Innovation and federal 18F. His current Piper Morgan project explores AI-assisted product development, while his government experience—from COVID19.ca.gov to federal digital services—demonstrates product thinking applied to public sector challenges. A Rosenfeld Media Expert and past mentor at Code for America and StartX, Christian bridges traditional product excellence with emerging AI capabilities to shape the future of product practice.
Erika Flowers is a design leader, strategist, and former member of the NASA Digital Service, where she led the agency’s human-centered AI-Readiness Initiative. With over 25 years of experience in product and service design across technology, healthcare, and government, Erika helps organizations bridge the gap between innovation and implementation. Her work focuses on preparing teams, leaders, and systems to adopt emerging technologies responsibly and effectively. Today, she advises organizations on service design, facilitation, and digital transformation, and teaches workshops that empower designers to lead the next wave of AI-driven change.
Benjamin Jackson is a creative technologist who’s obsessed with the future of work. A lifelong software engineer, he built the iOS news reader for the New York Times and served as director of mobile for Vice Media as it launched on cable across iOS, Android, Roku, and Apple TV. After Vice, Ben founded Hear Me Out, where he worked with clients such as Peloton and Atlassian to improve team performance through confidential listening tours.
Want to learn more? The full conference program is available for the Designing with AI 2026 conference!
More of a hands-on learner? We’ve got workshops all about design and AI, offered virtually this June.
Register now to secure your spot at the third annual Designing with AI conference! Trust us; you won’t want to miss it.
Last week in the Rosenverse, we hosted an insightful event with Catt Small about how to develop a product design idea that actually gets shipped.
Log into the Rosenverse to watch the recording.
See what you missed below.
April 30: Many designers create visionary artifacts (i.e. prototypes and decks) that generate excitement in the moment but do not make a meaningful impact on strategic planning. Teams that operate without the direction of a vision often have create roadmaps that feel reactive and fragmented. This results in user experiences that lack cohesion. In this talk, Catt Small shares a practical process for crafting a product vision that drives real decisions. You’ll learn how to identify the right moment for vision work, anchor future-state thinking in user and business realities, efficiently validate directional concepts, and translate long-term direction into roadmap-ready milestones. Let’s create vision artifacts that increase confidence, align teams, and shape strategy! Watch the recording »
This Q&A was drawn from the Rosenverse Live session.
A: A product vision is a strategic illustration of the customer experience you want to create. It matters because it gives teams a shared direction, helps align decisions, and keeps the work connected to both user needs and business goals.
A: The right time is when you need clarity on where the product is going and the team needs help making tradeoffs. Vision work is most useful when it can influence strategy, shape priorities, and create alignment before execution becomes locked in.
A: A vision gets shipped when it is grounded in real constraints, tied to a clear thesis, and translated into milestones that teams can act on. If the vision stays too abstract, it will inspire people but fail to change what gets built.
A: Many visions fail because the visuals are polished, but the underlying idea is weak or incomplete. High-fidelity mockups can create false confidence if they are not backed by a strong narrative, user insight, and a clear business rationale.
A: Product managers should be involved early and actively, because strong vision work needs to be rooted in product strategy and business reality. Their input helps make the vision more credible, more actionable, and easier to align across teams.
Catch up on last week’s recordings, and mark your calendar for upcoming events.
See you in the Rosenverse!
Many of us have been in the User Experience (UX) industry for quite some time—long enough to undergo major career pivots or even exit the field altogether. Change is always fascinating, and we think you’ll really enjoy this collection of Rosenverse Exit Interviews, curated by Uday Gajendar.
If you’ve been asking yourself the questions…What can I do after UX? What career paths are relevant for me as a UX designer? Is there a role out there for me beyond tech?
…Then this playlist is for you.
After years leading design at Google, ServiceNow, and Cisco, Greg Petroff made a bold move—leaving Silicon Valley for Sonoma County and traditional corporate leadership for fractional executive work. Now building two consulting practices while serving as fractional CDO for a fintech startup, Greg embodies what he calls being a “possibilitarian”—seeing opportunity in moments of change. We’ll explore his transition to the emerging world of fractional leadership and how he’s helping organizations navigate our AI-infused moment. Watch the recording »
A: Fractional work gives experienced leaders a way to stay impactful without committing to a single full-time executive seat. It can be a better fit when you want more autonomy, more variety, and a way to help companies that are ready for targeted leadership.
After two decades in Product Design, Cennydd Bowles is stepping away — not out of burnout, but disillusionment. The craft that once sought to elevate human experience now too often serves the false gods of metrics and efficiency, while the industry eagerly embraces approaches that lead to its own commoditization. Cennydd shares why he’s stepping away from the tech industry, what he’s learned about doing design responsibly in a system obsessed with mechanical efficiency, and how his next chapter—studying deception and morality in AI—might still bring us back to what design was meant to be. Watch the recording »
A: It means remembering that design is ultimately about people, not just outputs, metrics, or speed. Ethical design asks whether what we create is helpful, fair, respectful, and aligned with the kind of world we want to build.
After more than a decade of exploring the world as a user experience researcher, Chelsey Glasson found herself at a crossroads: continue in a traditional user research role or venture into something new. She chose the latter. Today Chelsey is in the early stages of a legal career, having just wrapped up her second year of law school. Remembering how scary it initially felt to even consider a career pivot, she’s excited to share why she made a change, some of the humbling and sometimes funny moments along the way, and how the skills she developed in UX continue to set her up for success today. Whether you’re contemplating a transition of your own or just curious about what a non-traditional UX-to-something-else journey can look like, Chelsey’s story offers insight, encouragement, and a bit of validation for wherever you are on your career path. And if you’re considering a change, know you’re not alone. There’s a whole community out here, cheering you on and excited to provide insight and empathy. Watch the recording »
A: Tech often encourages short-term performance cycles and constant calibration, which can make it hard to think about long-term career health. That environment can also intensify pressure around age, stability, and staying competitive.
Mary-Lynne Williams is the founder of Buffalo Firefly, a sound-healing and wellness company operating in Richmond, VA and Brooklyn, NY. Before stepping into this work, she spent over two decades in the tech industry as a product design leader, including roles at Microsoft, Meta, and Zillow, where she shaped complex digital products, led teams, and worked at the intersection of systems thinking, user experience, and human behavior. Her career in tech was successful by every external measure. Yet over time, Mary-Lynne began to recognize a growing disconnect between the work she was doing and the way she wanted to live in her purpose. She creates intentional spaces for rest and has recently opened a second location of her Sound Healing Center in New York City. Her story is not about leaving ambition behind, but about redefining success—trusting discernment, and choosing work that feels sustainable not just intellectually, but physically, emotionally, and spiritually as well. Watch the recording »
A: Trust your intuition and take yourself seriously. If something feels wrong in your body or life, that is information worth listening to, especially when you are considering a big transition.
What happens when the career you worked hard to build no longer fits the life you’re living? In this session, Ashley Sewall shares her decision to step away from senior UX leadership and the questions that followed. She reflects on burnout, identity, ambition, and the often-unspoken pressures of staying in tech—and explores what it looks like to apply design thinking to your own career. This is not a story about quitting, but about redesigning work to better align with values, health, family, and curiosity. Watch the recording »
A: It means treating your next chapter the way a designer would treat a problem: by exploring options, testing ideas, and making intentional choices instead of drifting into the future by default. It’s about building a life that fits your values, not just your résumé.
What do you do when you decide your skills deserve better problems? Sara Conklin spent 20 years doing UX work she was genuinely good at with people she truly liked. And somehow still went home empty most days. The problems felt too small. Worse, some felt like they were pointing in the wrong direction entirely. So she made a bet on herself. She walked away from a senior UX career in corporate tech and spent 18 months building something new from scratch. She journeyed through certifications, new knowledge, trial and error, and eventually a new career in residential electrification. Now, instead of maximizing clicks and driving consumption, she helps people feel more comfortable in their homes while reducing their bills and their climate impact. These days, she sizes HVAC equipment, pulls permits, coordinates subcontractors, and gets fossil fuels out of people’s homes. She also opportunistically uses her UX background to make the whole operation run better. This is a story about reinvention, risk-taking, and landing somewhere you’d never have predicted you’d find meaning. Watch the recording »
A: A tech background helps with product thinking, customer experience, systems design, and building better interfaces around a complicated purchase and installation process. Those skills matter because adoption is not just about the equipment; it’s also about making the whole experience easier to understand and trust.
Change is scary, but it’s easier when you know you’re not alone.
Last week in the Rosenverse, we hosted two events, including an Ask Me Anything (AMA) about a designer working in healthcare, and a session about team psychology and measuring success.
Log into the Rosenverse to watch these recordings.
See what you missed below.
April 22: Watch Eric Shumake’s rapid-fire AMA following his recent Rosenverse Live session. We dove deep into the practical strategies designers use to build influence, navigate regulated spaces, and drive UX investment within healthcare organizations. Watch the recording »
This Q&A was drawn from the Rosenverse Live session.
A: The hardest part is not designing screens; it’s getting enough influence to change how healthcare organizations make decisions. In healthcare, stakeholders care first about clinical outcomes, safety, compliance, and cost, so UX teams have to connect their work directly to those priorities.
A: UX matters because healthcare is full of high-stakes workflows where confusion can lead to errors, delays, and bad outcomes. Good UX helps patients, clinicians, and administrators move through complex systems with less friction and more confidence.
A: Start by translating UX findings into the language leadership already uses: risk reduction, operational efficiency, adoption, and patient safety. Small wins build trust, and trust opens the door to bigger influence over time.
A: AI is already showing up in documentation, decision support, and administrative workflows, but the real opportunity is in helping people understand and act on information. One especially important use case is patient education, where AI can translate medical jargon into plain language from admission through discharge.
April 23: How can design operations professionals measure success when we can’t always measure or control the results? Sometimes, even our best efforts don’t lead to the outcome we expected, but that doesn’t mean the work wasn’t valuable. I believe positive feedback from stakeholders always outweighs vanity metrics. In this talk, Johnny Michaelsen shares the core behaviors the Design & Research Operations team at Wise uses as the foundation for how their team operates. These behaviors focus on how to show up for the people being served, for each other, and importantly, for ourselves. They ultimately determine their focus and help build trust while delivering a positive change for the Design & Research environment across Wise. Finally, hear what was learned from a three-month experiment where the team at Wise aimed to measure themselves against these behaviors, rather than just measuring the results of their efforts. Dive into team psychology and explore why the right behaviors might actually matter more than metrics from final outcomes. Watch the recording »
This Q&A was drawn from the Rosenverse Live session.
A: Results can hide the real story, while behaviors show how a team actually works and whether it is building trust, clarity, and impact. Measuring behaviors gives us a better way to understand team health and to improve the things that lead to strong outcomes.
A: Three behaviors matter most for our team: delivering value now, being observant and of service, and creating visibility with clarity. Those behaviors keep the work practical, people-centered, and aligned to the needs of the organization.
A: Clear problem framing and sponsor alignment make prioritization much easier. When the team understands the real problem and the people behind the request, it can focus on work that creates the most value.
A: Trust comes from relationships, not just process. If you take time to understand what people actually need beneath their complaints or requests, you can create support that feels useful instead of procedural.
A: AI can speed up delivery and help with impact reporting, but it still needs clear direction. Used well, it helps teams move faster without losing focus on the behaviors that create real value.
Catch up on last week’s recordings, and mark your calendar for upcoming events.
See you in the Rosenverse!
Privacy concerns didn’t appear overnight—they’ve been building quietly alongside the technologies we rely on every day. Lou and Robert Stribley, author of Design for Privacy, explore how digital tracking, AI, and data sharing have reshaped the way personal information moves through the modern web.
Robert traces the growing privacy challenge from early internet tracking to today’s complex ecosystem of smartphones, online services, and AI systems. While many users understand that they’re trading data for convenience, few grasp how widely their information is distributed—or how easily supposedly anonymous data can be re-identified. As AI accelerates the ability to combine and analyze datasets, those risks are growing quickly.
Then the conversation turns to what designers can do about it. Robert outlines practical ways UX professionals can improve privacy outcomes, from collecting less data and avoiding deceptive patterns to improving language transparency and giving users meaningful control over their information. Despite the scale of the problem, Robert argues that designers have more agency and influence than they realize. Thoughtful design decisions can help protect users while also strengthening trust and long-term business success.
This Q&A is drawn from the podcast episode.
A: That’s exactly right — they didn’t appear overnight. The privacy challenges we face today have been building quietly alongside the technologies we’ve relied on every day. It starts with early internet tracking, the rise of smartphones, the explosion of online services, and now AI layered on top of all of that. Each wave added new ways for personal information to move through the world, often without users fully understanding what was happening.
Most people have some awareness that they’re trading data for convenience. What they rarely grasp is how widely their information is actually distributed once they’ve handed it over — or how many parties end up with access to it. I’ve looked at the cookie behavior on a single UK news site and found that it shared user data with over 600 third parties. Most visitors to that site have no idea.
A: Re-identification is one of the most underappreciated privacy risks out there. The common assumption is that if you strip personally identifiable information — your name, email address, phone number — from a dataset, the data becomes safe and anonymous. That’s simply not true.
One study found that 87 percent of the U.S. population could be uniquely identified using just three data points: zip code, birth date, and gender. That’s it. So when companies claim their data is “anonymized,” that word is doing a lot of work it often can’t support. And now AI is accelerating this problem considerably — the ability to combine and analyze datasets has grown dramatically, and that makes re-identification faster and easier than ever.
A: AI introduces risks at several levels simultaneously. At a data level, AI systems are trained on enormous datasets, and that data has often been collected in ways users weren’t fully aware of or didn’t meaningfully consent to. The FTC has been clear that quietly updating a privacy policy to collect data for AI training is deceptive and illegal — but it still happens.
At a design level, there’s a real risk that AI-generated interfaces will suggest or implement deceptive patterns simply because those patterns perform well. If you ask a generative AI tool to optimize a sign-up flow, it might recommend a pre-checked consent box or obscure opt-out language because historically those patterns increase conversions. Without a designer in the room who actively questions those recommendations from an ethical standpoint, those patterns can get shipped without scrutiny.
The pace of change is genuinely hard to keep up with. But that’s an argument for designers being more engaged in these conversations, not less.
A: There are several meaningful levers designers have — more than most realize. The first is data minimization: simply collecting less. Every piece of data you don’t collect is a piece of data that can’t be misused, breached, or re-identified. That sounds obvious, but in practice, the default in many organizations is to collect everything and figure out the use later. Designers can push back on that.
The second is transparency — not just in the legal, terms-of-service sense, but genuinely clear language that explains what data is being collected, why, who it’s shared with, and what users can do about it. Most privacy disclosures fail this test completely.
Third, avoiding deceptive patterns. Dark patterns in privacy contexts — pre-ticked checkboxes, buried opt-outs, confusing toggle labels — are unfortunately common. Designers who can identify those patterns have a responsibility to name them and advocate for something better.
And fourth, giving users meaningful control over their information. Not a control panel buried five levels deep, but genuine, accessible choices that people can actually find and use.
A: I understand why the scale of the problem can feel paralyzing. But I genuinely believe designers have more agency than they typically give themselves credit for. You’re often sitting in the room when the decision gets made. You’re the one who draws the form, writes the microcopy on the consent screen, decides where the privacy settings live in the navigation.
Those are not small decisions. They affect millions of people. And because designers tend to be the people in an organization who are most attuned to the user’s perspective and experience, they’re often uniquely positioned to raise the question: what does this design decision mean for the people who are going to use this?
That’s not a guarantee of success — organizational cultures vary enormously. But choosing to notice, and choosing to speak up, is the starting point for anything changing.
A: The business case is real and it’s growing stronger. The risks of data misuse or accidental exposure — reputationally, legally, and financially — are enormous. We’ve watched major companies face regulatory fines and public backlash over privacy failures that, in hindsight, could have been avoided with better design decisions earlier in the process.
But beyond risk mitigation, there’s a positive case: trust. Users who feel confident that a product handles their data responsibly are more likely to engage with it, stay with it, and recommend it. Privacy-respecting design builds the kind of long-term relationship with users that superficially convenient but privacy-compromising products can’t sustain. It’s not a constraint on good design — it’s a competitive advantage if you’re willing to treat it that way.
A: I hope they come away with a sense that this is their problem to engage with — not just legal’s problem, or the security team’s problem, or something that gets sorted out in compliance. Designers shape the experiences through which people interact with technology and hand over their personal information. That’s a real responsibility.
Privacy is ultimately about consent and control — allowing people meaningful say over what happens to their own information. That’s a fundamentally human-centered value, and human-centered design is supposed to be what we do. The two things are not in conflict. Once you see it that way, it becomes hard not to care.
Robert Stribley is a user experience design professional with some 25 years of experience. He works with brands both big and small across diverse sectors to provide thoughtful user experience solutions. He worked for many years at both Razorfish and Publicis Sapient, and recently started his own UX consulting company, Technique. Although he has particular experience designing for automotive and financial services, Robert has worked with companies as diverse as the American Red Cross, FreshDirect, JP Morgan, Mercedes-Benz, Travel Channel, and Women’s Wear Daily. He teaches user experience design at the School of Visual Arts in Manhattan. A chronic student himself, Robert earned degrees in journalism and English education and certificates in political journalism, privacy and data security, and global affairs. Read more »
0:15 – Meet Robert, Lou’s neighbor
1:51 – How Robert got into the privacy field
5:06 – Perceptions of privacy and the concessions we make
8:01 – Terms of Service – we accept them blindly – and why that can be risky
15:54 – 5 Reasons to use the Rosenverse
18:39 – What designers can do about data privacy
28:08 – Privacy tools and potential tools for users
32:38 – Robert’s gift for listeners
