The Approach

For 15 years I've led customer operations at high-growth companies—Zapier, Zendesk, ServiceMax—where the cost of getting this wrong isn't theoretical. It's attrition, revenue loss, and team burnout. I know what breaks under scale because I've had to fix it.

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I start inside your organization, using your team's knowledge, your customer data, and your leadership realities to design solutions that strengthen the post-sale customer journey and fit how your business actually operates. The sequence matters: redesigning workflows in collaboration with the teams who do the work comes before layering AI in. But high-potential workflows can move fast while the broader foundation is being built. The goal isn't a perfect strategy before anyone acts. It's identifying where AI can win quickly, low-risk and high-impact, and building structural clarity in parallel so those wins become repeatable and scalable. You get strategic clarity on structure, accountability, and technology adoption without destabilizing the culture that got you here.

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I bring emotional intelligence, direct operating experience, and a disciplined curiosity about what actually works. I continuously study AI and its practical application in organizations through MIT, Harvard, and ongoing independent research because responsible adoption requires leaders who understand it deeply. What I've learned reinforces what I've always known: technology doesn't fix structural problems. It exposes them.

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I've built and redesigned customer-facing operations across the growth curve. At a $50M ARR company approaching the gate to $100M, I designed the account management and customer success teams that protected and grew revenue, resulting in a 4% year-over-year increase in net revenue retention. At a $100M company, I restructured onboarding, introduced automation and accountability, and reduced time-to-value by 75%. And at a $35M company, I redesigned the support team's structure, hiring, and training, reducing costs by 22% without cutting quality or people.

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This work is iterative by design. The goal is that you leave more capable, not more dependent.