e14 Dana Chisnell on Ballot Design, Civic UX, and the 2000 Election

e15 Dr. Darren Hood On UX Maturity, Flying Cows, and Corporate Chaos

At some point in a UX career, you realize the problem isn’t wireframes. It’s tornadoes. Dr. Darren Hood has spent decades inside organizations watching projects get blown sideways by politics, confusion, shifting priorities, low UX maturity, and executives changing direction halfway through the work. This conversation is about what senior UX work actually starts to look like once you stop focusing only on deliverables and start paying attention to organizational behavior. We talk about stakeholder maturity, managing up, AI adoption, why “UX is dead” discourse is exhausting, and the difference between having an opinion versus having enough experience to recognize patterns. A lot of senior UX work isn’t designing interfaces. It’s learning how to function inside chaos without becoming part of it. Key Topics * UX maturity beyond organizational models * Why senior UX work becomes political * The difference between opinion and expert opinion * How experienced practitioners are approaching AI * Managing stakeholder chaos and “seagull management” * Why experienced UX people stop complaining and start reframing problems

E14 Part 2 Dana Chisnell on Scaling UX Inside the U.S. Government

What does it take to change how a 260,000-person organization thinks about the people it serves? Dana Chisnell took what she learned from elections and civic design into one of the hardest environments imaginable: the federal government itself. This is Part 2 of 2. Dana talks about her time at the U.S. Digital Service and DHS, where she built a user research practice inside immigration systems, figured out how to make developers care about real users, and eventually walked away in spring 2025 because she had to.

e14 Dana Chisnell on Ballot Design, Civic UX, and the 2000 Election

Dana Chisnell did not set out to work on elections. She was a freelance UX consultant doing work for Intuit and Cisco when she watched the 2000 election returns and thought, "this is an interesting design problem." That thought turned into a twenty-year arc through ballot design, federal government, and eventually a meeting with a sitting president. This is Part 1 of 2. Dana tells the story of the butterfly ballot, the gorgeous 350-page design guide that nobody could implement, and how a warmup presentation for Jared Spool led to an unexpected call from someone at the White House. The Corporate Underpants moments along the way are classics: great design that did not survive contact with the ecosystem, government websites that served the administrative process instead of the voter, and one very honest admission about not doing enough homework.

E13 Julie Francis On Journey Mapping, Alignment, and Why Your Work Isn’t Landing

Julie Francis and I have been solving the same problem from two different angles for over 20 years. She does it through journey mapping. I do it through alignment personas. This week we finally compared notes—and discovered we’ve been circling the same uncomfortable truth: it’s not about better deliverables. It’s about better alignment. We get into why the map isn’t the point, what “there’s nothing new in here” actually means, why shared documents are not shared understanding (cake wrecks, anyone?), and what it looks like to do senior product work when your job is facilitation, not output.

E12 Part 2 Josh Dulberger On Running An AI Product Lab

Seven months after Part 1 of my conversation with Josh Dulberger, the energy around AI hadn’t disappeared. But it had changed. Josh had left Zoom, joined a startup, watched it get acquired, and then stepped into running an internal AI product lab. Now the question wasn’t what could we do. It was what’s actually worth building. The work sounds exciting from the outside. Inside, it’s a lot of small experiments, dead ends, and decisions to stop. Teams build quickly. Test quickly. Most ideas don’t go anywhere. That’s the point. This is what happens after the initial wave. When the organization has to turn possibility into something real. Key Topics * What an internal AI product lab actually does * Running fast experiments with small teams * Why most ideas don’t make it * Deciding what not to build * What companies are actually looking for now