Product management is changing fast — and according to Julia Barham, many PMs are being pushed to the “left,” beyond delivery work into deeper discovery, customer insight, and strategic thinking. Julia joins Lou to discuss her forthcoming book, The Product Management Playbook: Create, Ship, and Optimize Winning Products, and why modern product managers need broader, end-to-end skills to thrive. Julia explains how AI and automation are reducing the amount of manual coordination and backlog management product managers traditionally handled — creating both anxiety and opportunity. As delivery work becomes easier, PMs are increasingly expected to spend more time understanding customers, validating ideas, collaborating across disciplines, and driving outcomes instead of simply shipping features. She also argues that great product managers succeed not because they know everything, but because they cultivate curiosity, build strong partnerships, and continuously learn across business, design, data, technology, and customer domains. The conversation also explores why many product managers feel disempowered inside organizations, the growing overlap between product and UX research, and how self-education, mentorship, and optimism can help professionals adapt during an uncertain AI-driven transition.   What You'll Learn from this Episode: Why product management roles are shifting toward discovery work How AI is changing delivery and project-management tasks The five core domains strong product managers understand Why curiosity is a product manager’s “X factor” How PMs can better partner with UX, engineering, and data teams Why many product managers feel disempowered today How self-education and mentorship accelerate PM growth What end-to-end product management really looks like   Quick Reference Guide: 0:18 – Meet Julia and learn why she wrote her new book 2:43 - Product managers shifting into customer rese–arch roles 5:29 - The dynamics of research shifting into the product space 8:44 - Other major messages of Julia’s book 11:55 - The common thread: curiosity 13:24 - Designing with AI virtual conference 14:10 - The insecurity of having breadth of knowledge but not depth 17:09 - The importance of self-education 19:02 - The ubiquitous attitude of “nobody listens to me or respects my position” and what to do about it 23:46 - Julia’s gift for listeners   Resources and Links from Today's Episode: The Product Management Playbook: Create, Ship, and Optimize Winning Products by Julia Barham https://rosenfeldmedia.com/books/product-management-playbook/  Dr. Marily Nika’s courses on Maven https://maven.com/marily-nika   Dr. Marily Nika on LinkedIn https://www.linkedin.com/in/marilynika  Hilary Gridley’s Couch-to-5K for AI https://couchto5k.ai/    Quotes: “Successful product managers usually operate across five different domains.”  “It’s not a book on theory; it’s a book on doing.” “You need to be a really good partner if you want to be a great product manager.” “The point is harnessing multiple superpowers to get that integrated thinking and develop a solution that’s going to work across what customers need, businesses need, and then can be scalable and sustainable.”   “You have to be curious. You have to spend time with your partners, get mentors, and learn to understand how design, data, technology all help you make a better product for customers and for your business.”

AI is opening the door to a new era of design—but most teams are still focused on making their existing work faster rather than reimagining what’s possible. Lou talks with Josh Clark and Veronica Kindred about their new book, Sentient Design, and what it takes to design truly intelligent interfaces. They introduce the idea of “practical magic”—starting with bold, even impossible wishes and then working backward to create real, deliverable experiences. Rather than defaulting to chatbots and efficiency gains, they argue that AI enables entirely new interaction models, from adaptive interfaces to agents that collaborate directly within products. The conversation also explores how design systems and past UX practices lay the groundwork for this shift, while designers themselves must unlearn habits that limit creativity. Through their “sentient design sprint” and “minimum magical product” framework, Josh and Veronica offer a structured way to move from imagination to implementation. At its core, this episode is a call for designers to reclaim their role as inventors—embracing AI not just as a tool, but as a new design material for creating more responsive, dynamic, and human-centered experiences. What You'll Learn from this Episode: Why AI is a new “design material,” not just a productivity tool How “practical magic” helps teams rethink what’s possible Why designers are stuck focusing on process instead of product innovation What adaptive, intelligent interfaces could look like in practice How the “sentient design sprint” turns ideas into real solutions What designers need to unlearn to work effectively with AI Quick Reference Guide: 0:13 - Meet Josh and Veronika and learn about their new Rosenfeld Media book 3:14 - Harnessing magical thinking with AI 9:19 - Moving beyond process, speed, and efficiency 13:11 - How designers can transition from tooling to inventing 16:53 - Exciting places the magic could take us 23:40 - 5 reasons to use the Rosenverse 25:52 - The Sentient Design Sprint 30:08 - The Sentient Triangle 33:36 - Is this applicable to non-traditional designers? Or what designers need to unlearn? 39:56 - Josh and Veronica’s gifts for listeners   Resources and Links from Today's Episode: Sentient Design: Crafting Intelligent Interfaces with AI by Josh Clark and Veronika Kindred https://rosenfeldmedia.com/books/sentient-design/ Designing with AI 2026 - June 9, 2026 https://rosenfeldmedia.com/designing-with-ai/  Enchanted Objects: Innovation, Design, and the Future of Technology by David Rose https://www.amazon.com/Enchanted-Objects-Innovation-Design-Technology/dp/1476725640  This is Running: A Celebration of the World of Running, Exploring the Culture, History, Brands, Races and People Behind It by Raziq Rauf https://www.amazon.com/This-Running-Celebration-Exploring-Culture/dp/1837330425?crid=10LYBYV063BKK&dib    Quotes: “We try to get in touch with the moments of emerging technology that help us to let go of the old ways of doing things and embrace the new, to think in terms of magical wishes.” “A ‘magical moment’ is that machines can understand our intent beyond just what we know to type.”  “The danger is we’re not endorsing magical thinking.” “First we retool, then we reorganize to get our process around that. And then we invent.”

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.   What You'll Learn from this Episode: Why shared language is critical for making sense of AI How Paul Ford approaches “rules” for using AI responsibly The risks of AI’s built-in flattery and “smooth” thinking Practical ways to use AI for prototyping without losing control Why verification systems matter more than trusting the model How younger generations actually view AI (less hype, more pragmatism) Why AI may be powerful—but not as historically radical as we think How to stay grounded and thoughtful amid rapid technological change   Quick Reference Guide: 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   Resources and Links from Today's Episode: Designing with AI conference - June 9, 2026 https://rosenfeldmedia.com/designing-with-ai/  Shell Game Podcast, by Evan Ratliff podcasts.apple.com/us/podcast/shell-game/id1753117762    Quotes: “In a world where product is very easy to spin up, the relationship is getting more and more important.”  “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.”  “There’s ways to mess with this stuff where I think you get to move forward and you get to think your thoughts without letting it take over.”  “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 of these technologies, I think is really dangerous because, God, you always want to hear it, especially when you're a boss.

As AI becomes easier and cheaper to deploy, designers face a new challenge: deciding not just what can be automated, but what should be. Lou Rosenfeld talks with Joy Kendi of Dalberg Design — and an upcoming speaker at the Designing with AI 2026 conference — about introducing AI into high-stakes systems where design decisions can directly affect access to healthcare, services, and critical resources. Joy shares examples from her work in public health systems, including an AI concept intended to help community health workers prioritize patient visits. What initially seemed like an obvious efficiency gain quickly raised deeper concerns around incomplete data, shifting real-world conditions, and the irreplaceable role of human judgment and community trust. Rather than treating AI as a decision-maker, Joy argues for designing systems where AI supports — but does not override — human expertise. Their conversation also explores how AI is reshaping the role of designers themselves. Joy makes the case that designers must move “upstream” in the process, helping define boundaries, risks, trust, and governance before automation decisions are made.    What You'll Learn from this Episode: How Joy Kendi defines “high-stakes” design systems Why automation can fail in public health contexts The risks of relying on incomplete or outdated data Why AI should support human judgment, not replace it How designers are moving upstream in AI decision-making What human-centered AI governance can look like in practice   Quick Reference Guide: 0:11 - Meet Joy and learn about high-stake systems 3:26 - Joy’s backstory 6:10 - Seeing beyond the everyday facade 8:55 - Why you need the Rosenverse 11:08 - Designing responsible AI for high-stakes public health decisions  16:06 - Why human judgment still matters in AI-assisted decision-making  18:29 - Designers must shape AI boundaries, not just interfaces  22:06 - Joy’s gift for listeners   Resources and Links from Today's Episode: Designing with AI 2026 https://rosenfeldmedia.com/designing-with-ai/    Quotes: “When I say high stakes systems, I mean systems where the design choices carry very real consequences beyond the typical interface or screen that a lot of designers are used to.” “The hardest question is not just can we build this tool. It’s also deciding whether we should automate some of these complex social decisions at all.”   “Even when the quality of data is good, and the data is available, there's more complexity to how human beings make decisions. A lot of that is also based on the social dynamics.”

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.

AI is reshaping product development faster than most organizations can even rethink how they work—and that gap sits at the heart of this conversation with product design guru Jeff Gothelf. Lou and Jeff explore why proven methods like Agile and OKRs so often become “process theater” instead of real change, and what it actually takes to shift organizations from output-driven cultures to outcome-driven ones. Jeff explains that most transformations fail because incentives still reward shipping outputs, not creating real value. Meaningful change tends to emerge only in pockets led by leaders willing to experiment and treat ways of working as something to test and evolve. They also explore how AI is shifting risk upstream—from engineering to vision, validation, and decisionmaking—making design and research more critical than ever. Along the way, they reflect on consulting as organizational therapy, the need to prove design’s value in the AI era, and why companies that relentlessly embrace new technology are best positioned to endure.

Jen van der Meer’s career path is anything but linear—spanning comparative religion, working on Wall Street, internet startups, and design education. In this thoughtful and timely conversation, Jen shares how her liberal arts background shaped her global perspective, eventually leading her to leadership roles at Frog Design, startups, and now Parsons School of Design, where she co-directs the MFA in Transdisciplinary Design. Jen challenges designers to go beyond the narrow scope of their titles or craft. Instead of trying to “convince” other industries of design’s value, she argues that designers must step outside their professional comfort zones, learn new languages—especially finance—and see themselves as co-conspirators in systemic change. With today’s precarious job market and the erosion of traditional design roles, Jen offers a compelling vision for designers to build collective practices, join interdisciplinary communities, and find purpose in transforming complex systems like health, energy, and finance. Her advice to students and early-career professionals? Focus on a system that needs fixing and start connecting with others who care.

AI isn’t just changing research tools—it’s reshaping how research itself happens. Lou chats with ResearchOps pioneer (and co-host of the upcoming inaugural UXR Tools Summit) Kate Towsey about the shift from linear workflows toward interconnected research systems where recruiting, knowledge management, repositories, and insights all function as part of a single ecosystem. Kate argues that future organizations will rely on “insights lakes,” structured collections of knowledge that anyone can query through AI interfaces, making research continuously accessible rather than locked behind reports. The discussion explores how tool vendors are evolving toward integrated platforms, why taxonomy and information architecture are even more essential in an AI-driven world, and how research operations professionals are becoming critical connectors across teams and technologies. Rather than replacing researchers, AI may free them to focus on identifying knowledge gaps and proactively generating insight. Kate ultimately offers an optimistic perspective: the future favors makers and experimenters—professionals willing to play, adapt, and help shape how AI is used responsibly within research practice.

What happens when someone moves from government UX research to shaping research for the broader industry? Lou talks with Maria Rosala, Director of Research at Nielsen Norman Group, about her role, her career path, and the value of research repositories. Maria shares what it means to lead research at NN/g and how her experience as a UX researcher in the UK Home Office shaped her perspective on research maturity and real-world practice. They explore how research repositories help organizations surface knowledge, avoid duplicate work, and support collaboration—and why people and culture remain just as important as the tools. Maria also discusses how AI could make repositories more powerful by surfacing connections and insights.

Survey research is in trouble—and Caroline Jarrett explains why. Returning to the podcast to preview the upcoming UXR Tools Summit, she and Lou Rosenfeld explore what’s really happening in the survey world and what researchers should be asking vendors right now. They discuss collapsing response rates driven by constant, low-value feedback requests and the growing sense that many surveys are performative rather than useful. Caroline argues for fewer, smaller, more targeted surveys that respect people’s time and actually lead to change. The conversation also tackles AI in research tools, from synthetic users to automated analysis, and why human judgment still matters. Caroline shares the key questions she plans to ask survey-tool vendors—especially around accessibility and panel management—and why researchers need better integration across tools and methods. She closes with a literacy-focused resource from the British Council tied to her passion for designing for people with low literacy.