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Redesigning an Enterprise Platform at Scale

Leading design strategy, systems, and a growing team through an 18-month, $1.6M engagement to modernize Meevo's highest-traffic product areas.

iPad showing Meevo Appointment Book redesign
Client Meevo (Millennium Systems International)
Duration March 2025 – September 2026
My Role Sole Design Lead (Year 1), then Staff-Facing Lead
Team 7 designers, 2 PMs, 1 Tech Lead, 1 Sr. Advisor
Investment ~$1.64M across 5 contract phases
Key Deliverables Appointment Book & Register redesign, 3-layer design system, design ops framework

The problem

Meevo was losing $1.7M in annual revenue to churn — and the UX was the primary driver.

The platform had been built over many years with inconsistent patterns, no unified design system, and a desktop-first approach in a world where front desk staff — often 16 to 22 year olds — expected mobile-first, touch-oriented interfaces. Competitors like Vagaro, Square, and Boulevard were winning on ease of use. Enterprise acquisition (European Wax Center) required modern UX and WCAG 2.1 AA compliance. And engineering teams had historically operated in silos, barely touching Figma.

This wasn't just a visual refresh. The product, the process, and the culture all needed to change.

Legacy Appointment Book calendar view with dark theme and dense grid
Legacy Appointment Book booking modal with cramped form fields
Legacy Register main screen with oversized color-coded tiles
Legacy Register service categories with color-coded grid
Legacy Register drawer manager with text-heavy layout

Appointment Book — Calendar view — The legacy calendar with a dark theme, dense grid layout, and toolbar overloaded with unlabeled icons. No touch optimization.

$1.7M in annual revenue lost to UX-driven churn
5.3M+ clicks per month on the Appointment Book alone
50+ feature gaps identified in legacy platform audit
3,500 business accounts on the platform

My role

This was my first Design Lead role. For the first year, I was the sole design lead across every workstream — owning strategy, mentoring 3 to 5 designers, managing stakeholder relationships, building the design system from scratch, and performing hands-on IC work on the Appointment Book, the most complex area of the product. All at once.

After a year of navigating that tension, I advocated for a second Design Lead to take the client-facing workstreams. That freed me to focus where it mattered most — staff-facing product work, the design system, and the design-engineering partnership.

Strategy & Vision

As sole Design Lead for the first year, owned design direction across all workstreams. Led feature prioritization, competitor research, and data-informed decisions for the most complex areas of the product.

Design System Architecture

Created a three-layer Figma library system from scratch. Defined design tokens, component documentation standards, and a readiness model that replaced "done/not done" with honest milestone tracking.

Team Leadership

Mentored designers across experience levels, ran structured critiques, created onboarding materials, and grew the team from a 2-person proof of concept to a 7+ person sustained design operation.

Process Design

Rebuilt how the team estimated, categorized, refined, and delivered work — from ticket taxonomy to sprint cadence to a 10-step handoff process that gave developers exactly what they needed.

The approach

Phase 101 — Mar–Apr 2025

Prove the vision

Future-state prototypes for 6 key workflows. Built to support an enterprise client pitch for European Wax Center. Introduced the "Opportunities" upselling concept.

Phase 102 — May–Jun 2025

Lay the foundation

I joined the project. Expanded Appointment Book workflows, began Register discovery, and started the first design system work. Mentorship into DL role began.

Phase 103 — Jul–Oct 2025

Scale the team

Grew to a full product team — 3 designers, formal sprint process, 10 product areas. Conducted a 50+ item feature gap analysis that became the redesign roadmap.

Phase 104 — Oct 2025–Jan 2026

Navigate pressure

Expanded to 5 designers under heavy delivery pressure. Managed shifting client expectations around speed vs. quality while keeping the team focused and steady.

Phase 105 — Jan–Sep 2026

Mature the operation

After a year as sole DL, brought on a second Design Lead to own client-facing workstreams. Launched a design system stabilization spike. Shifted to feature-level delivery with Kanban tracking. Established AI-assisted design ops framework for the full team.

Building the design system

Meevo had never had a design system. I built one from scratch — and then convinced a skeptical engineering team to actually use it.

I created a three-layer Figma library architecture: a Global UI Library for universal foundations (buttons, inputs, icons, tokens), a Staff-Facing Pattern Library for Appointment Book and Register patterns, and a Client-Facing Pattern Library for consumer booking and purchasing flows. The rule was simple — if a component appears in both staff and client products, it lives in Global.

When the Director of Product expected the system to be "complete in 2 weeks," I created a readiness model that reframed the conversation. Instead of done vs. not done, we tracked five milestones per library: Usable, Consolidated, Documented, Operationalized, and Governed. Each milestone had three dimensions — design usable, dev usable, and product usable. It gave stakeholders a clear finish line without pretending a design system stops evolving.

Three-tier design system architecture: Global UI Library, domain-level pattern libraries, and workstream files

"A design system is never done — it reaches states of readiness."

3 Figma libraries created
383+ design token bindings applied
5 readiness milestones defined
50+ components fully documented (and growing)
Current two-tier architecture: Global UI Library feeding directly into workstream files
New three-tier architecture: Global UI Library, domain-level pattern libraries, and workstream files
Milestone tracking board showing progress across Global, Staff-facing, and Client-facing libraries through 5 readiness stages
Color system showing light mode and dark mode tokens across primary, neutral, system, status, and category colors
Figma variables panel showing 85 color tokens with light and dark mode values
Component documentation for Cards showing anatomy, behavior, usage guidelines, and do/don't examples
Component showcase showing appointment booking components across desktop and mobile breakpoints with ready-for-dev status
Storybook component browser showing the Button component with variant controls and documentation

Current architecture — The original two-tier model: a single Global UI Library feeding directly into five workstream files, each with WIP and Delivery branches.

The new designs

Every screen went through a rigorous six-stage design process — from exploration and stakeholder review through delivery prep, componentization, and final handoff.

The redesign needed to work across every device a salon front desk might use — from wide desktop monitors to tablets propped on a counter to phones in a stylist's pocket. We designed every major workflow at four breakpoints: desktop, horizontal tablet, vertical tablet, and mobile. Here's the Appointment Book calendar — the highest-traffic view in the entire platform — across all four.

Desktop Appointment Book calendar — desktop breakpoint
Tablet landscape Appointment Book calendar — tablet landscape breakpoint
Tablet portrait Appointment Book calendar — tablet portrait breakpoint
Mobile Appointment Book calendar — mobile breakpoint

Beyond the calendar, we redesigned every major workflow across the staff-facing product — from appointment booking to the register and package management.

Redesigned Appointment Book — booking flow

Appointment booking — Streamlined booking flow with clear service selection, provider availability, and real-time conflict detection.

Redesigned Online Purchasing — packages

Online purchasing — Packages — Consumer-facing package purchasing with clear pricing, service breakdowns, and a modern checkout experience.

Redesigned Register — cart view

Register — Cart — Rebuilt cart experience with clearer line items, discount handling, and multi-tender payment support.

Redesigned Register — drawer manager

Register — Drawer manager — Simplified cash drawer operations with clear visual hierarchy and touch-optimized controls.

Transforming design–engineering collaboration

When I started, Meevo's dev teams barely used Figma and resisted UX involvement. By the end, I was invited into their Microsoft Teams developer space — something unprecedented for design.

The shift didn't happen overnight. I connected Meevo developers with our tech lead, advocated for developer presence at every step of the design process, and used my access to their Teams workspace to provide pre-QA design feedback — reducing friction before it reached formal review. I created an update contract for design system changes that told developers exactly what changed, whether it was visual or behavioral, and whether to consume the update now or later.

The design system became the bridge. With developers increasingly using AI-assisted "vibe-coding" from Figma assets, the quality of our component library directly impacted the quality of their output. The framing I used with stakeholders: "Quality you feed the design system now equals the quality AI produces in 3 to 6 months." That message landed.

Before

  • Dev teams barely used Figma
  • Resisted UX involvement
  • No reusable component structure
  • Inconsistent UI across features
  • Design and engineering in silos

After

  • Building codebase aligned with design system
  • Using Storybook with component repo
  • Leveraging AI from Figma assets
  • Commenting directly in Figma files
  • Weekly design-dev sync established

AI as a design accelerator

My approach to AI has two phases. First, I need to fully understand what a tool is actually capable of — not the marketing pitch, but the real mechanics. Then I figure out where those capabilities can be meaningfully applied to the work my team is doing. I learned quickly how Claude Code could be leveraged for elaboration, strategy, documentation, and prototyping — but I didn't stop at using it myself. I made it so every designer on the team could do the same.

Shared AI workspace

Created a GitHub repository that served as a shared context folder for Claude Code across the entire design team. Designers could push and pull updates to project context as they worked — giving every AI session the full picture of the engagement, not just one person's slice of it.

Team enablement

Didn't just implement AI tools for myself — I provided training, helped every designer set up their environment, and built a process framework that empowered the team to become AI power users on their own.

Design elaboration

Established a structured process for AI-assisted ticket elaboration — context gathering, requirements documentation, scenario mapping, and edge case identification — all before any design work began.

UX strategy & prototyping

Used AI for UX strategy development, annotated design deliverables, and building highly detailed, fully functioning prototypes — accelerating work that would normally take days into hours.

Design system documentation

Leveraged AI to establish component documentation standards, generate initial drafts, and maintain consistency across all three Figma libraries.

Design-dev bridge

Positioned the design system as the AI pipeline: Figma → Storybook → AI-assisted development. Structured assets so AI could consume them reliably — quality in, quality out.

Leading through complexity

Meevo's needs shifted constantly. Their product team was brand new — most of them newer to the company than I was to the project — which meant priorities, requirements, and even goals could change on a dime. Sometimes they didn't yet know what they wanted or needed.

That kind of chaos requires a team that doesn't just react but actively works to stay ahead. I ran countless internal working sessions where we whiteboarded every possible pathway forward — diagramming process improvements, realigning on delivery speed, and finding ways to maintain quality without slowing down. When things went sideways, we didn't panic. We regrouped, reframed, and showed up the next day with a plan.

Restoring and maintaining stakeholder confidence became a constant thread throughout the engagement. The work itself mattered, but so did how we communicated it. I shifted the team toward visible progress, feature-level delivery, and clear prioritization — reducing ceremony and focusing on the things stakeholders actually needed to see. Over 18 months and 5 contract renewals, we proved that a design team can be a steady, adaptive partner even when the ground keeps shifting underneath.

Outcomes

Product impact

  • Redesigned the highest-traffic product areas (Appointment Book, Register) for a platform serving 3,500+ businesses
  • Established WCAG 2.1 AA accessibility as a first-class design constraint
  • Defined measurable success metrics: 20% fewer clicks, 15% opt-in, minimum 4-star survey rating

System impact

  • Created a three-layer design system architecture — the first centralized source of truth in the product's history
  • Applied 383+ design token variable bindings across core components
  • Built a readiness model adopted by product leadership for milestone tracking

Team impact

  • Grew team from 2-person proof of concept to 7+ person sustained design operation
  • Transformed design-engineering relationship from adversarial to collaborative
  • Maintained client relationship through 5 contract renewals (~$1.64M total investment)

Process impact

  • Designed a ticket categorization system the client adopted organization-wide
  • Created a three-stage review process and 10-step handoff framework
  • Positioned the design system to enable AI-assisted development at scale

What I learned

Meevo was the project that shaped me as a design leader. It taught me that designing the process is as important as designing the product — and that the best systems work isn't just about components, it's about trust, communication, and knowing when to push back versus when to adapt.

I learned to use data to decide where design effort matters most: 83% of locations didn't use clock-in indicators, so we gave it appropriate — not maximum — attention. I learned that stakeholder management is a design skill. And I learned that AI isn't something to be afraid of or to overhype — it's a tool that, when integrated thoughtfully, makes space for better human decisions.

If I could do it all again, I'd push earlier for the second Design Lead role and resist the instinct to absorb every gap personally. But the scars from that tension are part of what make me better at the work now.

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How this site was built

I'm going to say the quiet part out loud: AI built this website. And I'm proud of that.

Most people hide behind the fact that they use AI to create things. I want to flaunt it — because I think the way you use AI says more about you than whether you use it at all.

I've spent 16 years trying to deploy the portfolio website I always envisioned. I tried everything a non-coder could try — Webflow, Wix, Squarespace, literally just shipping a Figma prototype as my portfolio for the last few years. My most recent attempt had me deep in Framer, convinced I'd finally cracked it. Another unfinished project. The truth is, when you're working full time leading design teams, there's never enough time or energy left to also build and maintain your own site. The vision was always there. The bandwidth never was.

AI changed that equation entirely.

I designed every screen, every interaction, and every detail of this site in Figma — the same way I design everything. Then I used Claude Code to bring it to life, guiding it step by step through layout, styling, animation, and content. Every decision was mine. Every pixel was intentional. The AI was the tool that finally closed the gap between what I could envision and what I could ship.

But the site itself is just one output. The real unlock came from the way I've been working on projects like Meevo — building an AI-assisted design operations framework around markdown files, GitHub repositories, and context systems that keep multiple AI agents working with the most comprehensive understanding of the project possible. Over 18 months of leading that engagement, I accumulated a massive amount of project data: strategy documents, design rationale, stakeholder feedback, research findings, system documentation, the works.

So when it came time to write the case studies on this site, I didn't start from scratch. I pointed AI at all of that structured context and used it to help me aggregate, synthesize, and draft the narratives you're reading here. Because why wouldn't I? The craft is in the curation, the framing, and the judgment. The AI handles the grunt work that used to make case studies the thing designers never finish.

The result is the thing you're looking at right now — a portfolio that actually represents who I am, built the way I believe design should work. Not despite AI, but because of it.