Leadership approach
Create direction. Develop people. Make quality repeatable.
Effective design leadership improves the conditions around the product: the team’s judgment, the standards it shares, and its ability to deliver together.
- Connect the business need
- Develop the team
- Establish shared standards
- Deliver and learn
01 / Direction
Connect platform investment to a real delivery need.
Managed UDS as an internal product and used the Merchant & Supplier Portal as a proof point for continued investment. Requests were prioritized against business impact and delivery capacity.
Shaped $7M–$13M in investment plans within a shared $52M director-level portfolio. That was influence and planning with partners, rather than sole ownership of the entire portfolio.
02 / People
Give people meaningful room to grow.
Led 25+ direct reports across design, research, engineering, data science, product and Scrum. Team development included a Pricing designer’s stretch assignment into global navigation, regular QA feedback, and mentoring a backend engineer into team leadership.
His LinkedIn recommendation describes expanded skills and coordination across US and India contributors. It reflects the value of stretch assignments and regular feedback.
03 / Operating model
Give standards an owner and a contribution path.
UDS combined shared foundations with a council, contribution review, accessibility checks, QA, versioned release and deprecation. Participating-team funding supported continued expertise and delivery services.
This is the work that helps a design system remain useful after launch. The operating model should make participation possible while keeping the experience coherent.
04 / Responsible innovation
Expand capability while retaining judgment.
In the merchandising workflow, UX delivered production frontend code while engineering focused on APIs and services. Taught prompting, context and token management, automation and reusable skill development. A Markdown-based design system, shared repository and contribution guardrails gave UX, engineering, product and data-science partners a common operating model.
Developed the team’s ability to lead AI-assisted work rather than simply generate more output. Explicit ownership boundaries kept UX focused on interfaces and engineers on APIs, backend services and specialist work. Human review remained part of the process, alongside evaluation of quality, rework, operating cost and user outcomes.
See these principles in practice.
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