Corporate Underpants

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

E12 Part 1 AUDIO Josh Dulberger On Building AI Inside Zoom

FINALLY! A new (old) episode of Corporate Underpants has dropped! This is a two parter with Josh Dulberger. Part one is the story of what happened when AI “showed up” at Zoom. Spoiler alert: it didn’t show up as a clear opportunity. It showed up as noise. Josh was leading AI product work at Zoom when suddenly everyone had an idea, a request, or a question. Slack filled up. None of it connected. It was the organization trying to react to something it didn’t understand yet. What followed wasn’t a clean strategy process. It was sorting through fragments. Figuring out which signals mattered. Ignoring a lot that didn’t. Somewhere in that, they landed on something simple: Meeting summaries. Not because it was flashy, but because it finally made something people already had usable. This is what senior product work looks like in moments like this. Less building. More making sense of chaos. Next week you can tune in for Part 2: What happened seven months later when the hype turned into actual product work in the AI lab he runs today.