A note on AI design leadership

If you're hiring for an AI design leadership role, you've probably seen a lot of portfolios this week. People who've worked adjacent to AI products, or who recently rebranded themselves as AI designers because the market shifted. I get it — the moment demands it.

I've been building in this space before it had a name. At ServiceNow, I led the design of an enterprise-wide AI deployment across Strategic Portfolio Management — not a feature, not a concept, a live system that real teams depend on every day. I established how AI agents surface, how they behave, what they say and don't say, and how you build trust with an enterprise user who's already skeptical. That work is in production across 100,000+ users.

What I've learned is that the biggest risk in AI product design isn't making something too complex. It's making something that feels powerful in a demo and exhausting in real life. The gap between those two things is where design leadership actually lives — and it's where most organizations are losing right now.

I know how to close that gap. I know how to take an ambiguous AI capability, work backwards from a real human need, and ship something that people actually want to use. And I know how to do it in a way that earns trust from engineering, earns buy-in from product, and earns respect from the executives in the room — because I've done it, not just described it.

If you're building a team around this and you want someone who's already lived the hard version of this problem — I'd love to talk.