A Design Ops Girl in a Dev Ops World
Summary
Key Insights
-
•
The ambiguity of the word 'We' at WeWork necessitated developing a unique internal syntax for clarity.
-
•
WeWork operates at an exceptionally rapid pace, experiencing a week’s worth of challenges daily.
-
•
Program managers were initially misunderstood as 'expense of routers,' highlighting a gap in understanding their unique skills.
-
•
Learning people’s origin stories reveals their motivations and helps build deeper connections beyond just knowing roles.
-
•
The Red Tech mission was formed from three distinct waves of teams with very different cultures and histories.
-
•
Introducing simple, fundamental agile scrum training helped unify teams with varying levels of scrum knowledge.
-
•
Quarterly retrospectives with strict ground rules and three focused questions unlocked honest dialogue and revealed emotional undercurrents.
-
•
Mapping agile stories directly to OKRs connected team efforts to company goals and surfaced cross-team collaborations.
-
•
Implementing peer recognition through the Silver Heart Hat Awards boosted morale and peer appreciation visibly and inclusively.
-
•
Building or finding a 'tribe' of trusted collaborators is essential for emotional support and navigating rapid organizational change.
Notable Quotes
"When I talk about We, am I talking about You and Me, or the company itself? The word We can get really confusing."
"The volume coming at me every day was like a week’s worth of work compressed into one day."
"Program managers are just expense of routers—what they missed was the how, that secret sauce of EQ."
"Asking someone’s origin story gets you their why, not just the what."
"There are at least six definitions for desks at WeWork—context matters."
"Many team members were faking scrum until they made it; they used the words but didn’t know the practice."
"What started off poorly but improved during the quarter is where all of the magic happened in retrospectives."
"Quarterly retros are sacred; what happens in retro stays in retro to create trust and honest conversations."
"Multiple teams were supporting the same goals in different ways, and that led to meaningful cross-team conversations."
"Find the people with whom you can lock eyes—those are your tribe, your support system."
Or choose a question:
More Videos
"A taxonomy system is basically a way to tag different findings and reports so you can find relationships later."
Tony TurnerCapturing Deep Insights
September 30, 2021
"Centering connection and relationships rather than transactions is the true happy path in design."
Frances Yllana Ann Buechner Jess Jones Betsy RamacciaD.E.A.R.R. Diaries (Discipline, Experience, Architecture, Reflection + Revolution)
November 16, 2022
"I’m drowning trying to create an understanding of our target audience for a new feature, but that leaves me no time for usability updates."
Anna Poznyakov Richa PrajapatiGet The Most Out Of Stakeholder Collaboration—and Maximize Your Research Impact
March 12, 2021
"Design maturity shifts focus from evangelism to operations as organizations strengthen their design impact."
Sarah WilliamsA Framework for CX Transformation
June 11, 2021
"Good UX is good business."
Product and Design at Bloomberg: A 15-year Evolution
December 6, 2022
"We resisted the temptation to squash diversity of usage because we thought we’d learn from it."
David CroninThe GE Design System and Thoughts about Craft at Scale
May 13, 2015
"We need to be genuinely curious not just about our customers, but also about our colleagues and the technology behind AI."
Liwei DaiThe Heart and Brain of the AI Research
March 31, 2020
"Confidence scores from the model are not a good idea because the model has no memory."
Peter Van DijckHands-on AI #1: Let’s write your first AI eval
October 8, 2025
"Empathy means constantly going back to the people using the tools and hearing their feedback."
Jon Fukuda Amy Evans Ignacio Martinez Joe MeersmanThe Big Question about Innovation: A Panel Discussion
September 25, 2024
Latest Books All books
Dig deeper with the Rosenbot
What human responsibilities remain critical when integrating automation and machine learning in design?
How can designers advocate for a role in AI product development within engineering-heavy teams?
What tools enable local, privacy-focused integration of smart home energy data without relying on cloud services?