Generalistas learn what the work demands, when it demands it. They're adaptable, undeterred, and velocity-focused.
In the age of AI, they're the superstars.
I'm John Garvie, Head of Design at Evisort AI (Workday).
I'm documenting how my team and I are becoming Generalistas—and interviewing design leaders across the industry about how they're navigating the same shift.
Generalistas are professionals who learn skills on-demand to solve problems their specialization can't handle.
Not by going back to school. Not by quitting their jobs. But by learning what the work demands, when it demands it, while doing their actual work.
Learn what the work demands, when it demands it. Don't wait for formal training or permission.
Don't let skill gaps stop you. Cross role boundaries to solve problems.
Learn just enough, just-in-time. Ship while learning, learn while shipping.
The outcome: You become the person who figures it out. You become unblocked. You become the superstar. You align with the age of AI.
Design roles are expanding beyond traditional boundaries. Here's what's changing across the industry.
The old model
Designers make mocks. Engineers build prototypes.
The new reality
Designers use AI tools (v0, Claude, Cursor) to build functional prototypes themselves
The shift
From static screens to interactive experiences
The outcome
Faster iteration, better feedback, less handoff friction
The old model
Multi-week studies to gather and synthesize insights
The new reality
AI helps analyze data, validate hypotheses, and surface patterns faster
The shift
From depth-only to depth + velocity
The outcome
Insight to decision in days, not weeks
What's changing
Hiring for AI fluency, prototyping ability, and cross-functional breadth—not just traditional design skills
The shift
From specialized roles to T-shaped generalists
The outcome
Smaller, faster teams that ship more
How design leaders at top companies are navigating the shift to AI-augmented work.
This isn't just my journey. Design leaders across the industry are grappling with the same questions: How do we stay relevant? How do we lead teams through this transition? What skills matter now?
I'm sitting down with design leaders from companies like Meta, Google, Stripe, Figma, and more to explore how they're adapting their craft, their teams, and their careers for the AI era.
How senior design leaders are reskilling themselves and their teams to prototype with AI, integrate AI features, and maintain design excellence.
Research leaders share how they're using AI to synthesize insights, validate hypotheses, and move from insight to decision faster than ever.
These conversations will be published as part of the newsletter. Subscribe to get notified when new interviews drop.
Subscribe for InterviewsWork-integrated learning. No bootcamps. No quitting your job.
Can't move forward without X skill
Need to learn Y to solve this problem
AI tools + daily practice embedded in work
Ship something using the new skill
Document what worked, what didn't
This is work-integrated learning. You don't leave your job. You learn while doing.
We're living through the biggest economic shift of our lifetime. AI is reshaping entire industries. The nature of work is changing faster than institutions can adapt.
Unlike past technological transitions, there's no safety net. No retraining programs. No time to go back to school. Workers need to reskill while actively working, and most are navigating this alone.
Specialists are struggling. AI automates narrow tasks. Market consolidation demands versatility. Rigid role boundaries create bottlenecks.
Generalists are thriving. They adapt rapidly. They solve cross-domain problems. They're resilient to disruption.
The future belongs to Generalistas. T-shaped professionals who combine:
This isn't about being mediocre at everything. It's about strategic breadth that amplifies your deep expertise, and the practical ability to build new skills while keeping your day job.
This is both personal and societal. Individually, becoming a Generalista makes you resilient. Collectively, we need a new model for continuous reskilling that doesn't require leaving the workforce.
John Garvie, Head of Design @ Evisort AI (Workday)
Former Director of Design at Amplitude and Senior Design Manager at Uber for Business.
In 2017, I was a UX Research specialist at LinkedIn. I built and led research teams across B2B products: Marketing Solutions, Sales Solutions, LinkedIn Learning. I was good at it. I was deep in my vertical.
But over the next 8 years, something shifted. I moved from Research Lead to Research Manager to Head of UX Research at Uber Eats (leading research for 130M+ users globally). Then I made my first major transition: from research to design leadership.
From 2022 to 2025, I led design strategy and execution for Uber for Business, then joined Amplitude as Director of Design to strengthen design talent and accelerate AI integration. Now I'm at Evisort AI (acquired by Workday), leading design for AI-powered enterprise software.
Along this journey, I stopped being just a researcher. I became a designer. A strategist. An AI integrator. A team builder. Not because I wanted to be a jack of all trades, but because the problems I wanted to solve required it.
But this is bigger than individual career growth. I've watched talented designers, researchers, and product people struggle during transitions because their skills were too narrow. I've seen how quickly AI shifts what's valued. I've experienced firsthand how difficult it is to reskill while working full-time.
There's a broader need here: people need practical frameworks for continuous learning that don't require leaving the workforce. The economy is changing faster than traditional institutions can respond. We need new models for ongoing adaptation.
Right now, I'm learning to code, experimenting with AI tools, and figuring out how to maintain velocity when my core UX skills hit their limits.
My team is doing the same: using AI to prototype, research, and solve problems that used to require specialists.
We're not experts in AI or coding. We're Generalistas: learning what the work demands, when it demands it.
This newsletter documents our experiments, mistakes, and discoveries.
Columbia University • 5K+ LinkedIn followers • Published author on UX thinking • TMRE 2018 Speaker • San Francisco