My leadership style is people first, some call it servant leadership. I believe it's the only approach that actually works. Great things get built by people who feel trusted, challenged, and supported, not managed.
Five building blocks of my leadership persona:
Catalyst (Bias toward action, not analysis paralysis)
Believer (Doing the right thing, especially when it's inconvenient)
Deliverer (I follow through. If I said it, I do it.)
Coach (My job is to make the people around me better, not to be the best person in the room)
Self-Believer (Resilience and risk tolerance aren't things I perform. They're how I'm wired.)
The answer usually comes from within the team
My job is to ask better questions, not provide all the answers.
Walk the floor
You can't help improve work you don't understand. I talk to people daily: engineers, designers, data scientists. Not to check in, but because proximity to the real work keeps my judgement honest.
Be the change you want to see in others
The best way to get people to adopt a mindset, process, or tool is to have them see an example of it working well.
Over the years, I have discovered what works and what doesn’t in my leadership. Here are some of what I believe about AI product leadership, thoughts and approaches:
Technical fluency is non-negotiable, and AI makes it accessible
I'm a designer who codes. I ship real systems: on‑device AI tools, agentic workflows with hard safety rails, and production deployments in environments where failure actually matters. AI has amplified what I can do as a builder by an order of magnitude, and I believe that's now the baseline expectation for anyone leading AI product teams.
I hold a high bar for this on my teams too. I don't expect every PM or designer to write production Python, but I do expect them to understand what's happening inside the systems they're shaping. You can't make good product decisions about models you've never touched.
AI as meaningful leverage and strategy
The best products are not the ones with the most AI in them. They are the ones where intelligence makes something meaningfully better, a decision becomes clearer, a workflow becomes faster, or a user can act with context they could not reasonably hold on their own.
Most products do not need AI added to them. They need better judgement about where AI belongs, where it does not, and what has to be true before it earns a place in the experience.
The teams that get this right treat design, product, engineering, and evaluation as one system. They do not ask, "Where can we add AI?" They ask, "Where does intelligence create real advantage, and what guardrails make it safe to use?"
Lead through expertise, not authority
Effective AI product leaders need genuine depth in their discipline. Not to be the best engineer or researcher on the team, but enough to be a credible thought partner for the people doing the hardest work. Research shows that leaders being an expert in their field gain trust quickly and great for team morale too. Generic management doesn't cut it when your team is building at the frontier.
Love the problem, not the solution
Starting with a solution is like building a key without knowing what door it opens. (Ash Maurya said that. Still the best framing I've found.) I still find myself coaching teams on this constantly, the pull toward the solution train is strong, especially in AI where the technology feels like it should be the answer to everything.
Hire for trajectory, then grow capability deliberately
Highly performing teams don't just happen, they are made. I track individual skills deliberately and hire to fill real gaps, so every new person raises the floor. I also give teams real ownership of who they work with; after all, they are going to spend a lot of time working together.
The best outcome is when the team doesn't need me to succeed
I set a high bar and then get out of the way. My job is better process, space to experiment, timely feedback; not being the final gate on every decision. The goal is a team that can operate with full autonomy and still produce work worth being proud of.
Build and coach to pay it forward
I'd rather show someone how to do something than do it for them. Learning by doing, jumping in the deep end, making the mistakes, sharing what you found; that's the culture I try to build. It’s worth doing.