VML × ConEdison

Managing two Agile pods simultaneously means holding design coherence across parallel workstreams that often pull in different directions. Customer Billing and Account Management share a platform but diverge in complexity, data density, and stakeholder pressure. My role is to make sure both move with intention.

Day to day that means working across the full org chart, managing stakeholder expectations through prototyping and presentations, facilitating collaborative UX discovery sessions, and navigating the competing constraints of legal, copy, frontend, backend, and Scrum Masters without losing design quality in the process.

• Lead design strategy and feature-level UX discovery sessions across both pods
• Manage stakeholder expectations through high-fidelity prototypes and executive presentations
• Partner with Legal and Content teams to ensure copy, compliance, and design are aligned before engineering picks up a ticket
• Collaborate with Creative Directors at VML and ConEdison to maintain brand voice and visual consistency
• Mentor designers on the pod: critique structure, career growth, and raising the quality floor

I introduced AI tooling into the design workflow incrementally, starting with the highest-friction areas and building team confidence before expanding. The goal wasn't adoption for its own sake; it was measurable speed and quality improvements that both design and engineering could feel.

• Prompt-driven wireframe divergence to explore 4–6 layout directions in the time it previously took to produce one
• AI-assisted copy generation paired directly with content designers for faster UX copy iteration
• Generative component variants in Figma to stress-test design system edge cases before engineering encounters them
• AI-supported accessibility checks integrated into the review workflow, catching contrast, label, and focus order issues before handoff
• Prototype acceleration using Framer and AI-enhanced interaction patterns to demonstrate complex behaviors to stakeholders without engineering investment

Building and maintaining the ConEdison design system requires holding two things in tension: the creative flexibility teams need to solve real product problems, and the structural consistency that makes a platform serving millions of customers predictable and trustworthy.

I maintain the Figma component library with a token-based architecture (primitives → semantic → component) that maps directly to the frontend implementation, reducing the translation layer between design and code and making brand guideline updates propagate automatically across all surfaces.

• Token-based Figma system: primitives → semantic → component, mirroring the CSS token structure used in production
• Component documentation with usage guidelines, state specifications, and explicit do/don'ts for engineers and designers
• Brand guideline stewardship, maintaining ConEdison's visual identity across web portal, mobile web, and tablet breakpoints
• Design system contribution model: clear criteria for extending vs. creating new components, preventing fragmentation across pods

The technology is the easy part. Getting a team of designers and engineers to shift how they work, especially in a regulated, enterprise environment with legacy process inertia, requires sustained investment in trust, demonstration, and psychological safety.

The Lunch & Learns that landed weren't the ones with the most impressive demos. They were the ones where I solved a real problem the team had that week, live, using AI. That's the proof of concept that changes behavior. Design leadership in an AI era isn't about knowing the most tools; it's about knowing which tool to reach for, and making that judgment legible enough that your team can replicate it.