I'm May—a product designer1 who thinks in systems, not screens. I define the problem, then ship the answer.2 Based in London.3
The designer you call when nobody knows what to build yet. 8+ years as a staff-level product designer, most of it as the only designer in the room—which means I've learned when to be scrappy and when to obsess over details.
I stay on the bleeding edge of AI tools—Cursor, Claude, V0—because they collapse the gap between "what if" and "here, try this." I validate cheaper, so I say "let's try it" instead of "let's debate it." But AI can't reframe a problem, navigate a room full of competing stakeholders, or decide what not to build. That's the work I do. I measure by what shipped and how behaviour changed, not the Figma file.
Drawn to ambiguity, open-ended tools, and problems that don't have obvious solutions. Poor design choices are expensive—not just in rework, but in lost trust, missed revenue, and teams building the wrong thing. I've shipped across fintech, logistics, AI/ML, and enterprise SaaS—each time figuring out what mattered before anyone handed me a brief.
At a payments company, I designed a 0-to-1 sales platform for 300+ field agents. At Gophr, sole product designer for 3+ years—shaped strategy with founders, scoped roadmaps, made trade-offs daily. At Eigen, a B2B SaaS, rebuilt the design team and turned document review into collaboration: 87% faster processing.
London-based. I've spent most of my career doing 0→1, and I thrive on ambiguity. I'd rather ship something real than polish something theoretical. "Let's try it and see how it feels" is how I work. Kind, ambitious, pragmatic.
I treat collaboration as a multiplier—the best outcomes I've delivered came from making everyone in the room smarter about the problem, not from designing alone. I have the best WhatsApp sticker library you'll ever see, and I will absolutely send you one mid-meeting if the moment calls for it.
I'm May—a product designer who thinks in systems, not screens. I define the problem, then ship the answer. Based in London.
Staff Product Designer · 8+ years across fintech, logistics, AI/ML, and enterprise SaaS
66% of UK revenue came from sellers the company couldn't see or track.
0-to-1 Sales Platform.
Progressive disclosure lets agents capture deals in 10 seconds — compliance data follows later.
Millions of fans, 10,000+ negative reviews. The app crashed when it mattered most — live matches.
Reliability Over Features.
40% fewer features at launch, focused on what must work flawlessly. Trust rebuilt through stability, not feature count.
Sole designer across two platforms, 10K+ enterprise accounts, 10K+ couriers. No system, no docs, no process.
Dual Design Systems.
Atomic Design systems for both platforms. From chaos to 30% faster feature delivery and a seat at the strategy table with CEO/CTO.
Enterprise document review forced sequential processing. Every queued document meant delayed decisions and revenue.
Collaborative Intelligence.
AI handles routine extractions, experts handle edge cases. Review became teamwork, not gatekeeping.
Manual ad booking capped how many campaigns could run. Sales spent 70% of time on admin instead of relationships.
Digital Self-Service Platform.
Designed for psychological safety first — familiar patterns and fallbacks encouraged adoption over resistance.
8+ years across fintech, logistics, AI/ML, and enterprise SaaS. End-to-end ownership shaped by startup constraints and complex stakeholder environments.
Payments Company — Designed 0-to-1 internal sales platform: lead capture, deal management, lifecycle governance. Resolved cross-team terminology confusion that changed backend architecture. Delivered progressive disclosure enabling 10-second deal capture for 300+ field agents.
Digital Consultancy (Contract) — Led discovery for complete app rebuild serving millions of fans globally. Reframed project direction from "add features" to "rebuild trust through reliability"—by synthesising 10,000+ app reviews that revealed the real problem. Created design system with React/Tailwind foundations unifying two competing brands.
Gophr — Sole designer for 3+ years, serving 10K+ enterprise accounts. Built dual design systems from inherited chaos, drove 40% engagement increase and 47% dev efficiency boost. Partnered directly with CEO and CTO on product strategy.
Eigen Technologies — Transformed single-user document review into enterprise collaboration system for Goldman Sachs, Deloitte, ING. 87% faster processing, 75% fewer errors, 93% satisfaction. Led design across 6 engineering squads post-restructure, mentored 2 designers through delivery.
Coforge — Led projects for Channel 4, British Library, Santander. Channel 4: 2.5x ROI, 89% operational efficiency, 98% error reduction. British Library: 45% navigation reduction, satisfaction 42%→87%. Built WCAG-compliant design systems.
Freelance — 20+ projects with end-to-end ownership: Art Basel, S&P Global, Sun Life, Mercer, Viiv Healthcare, A&O Shearman, Swiss Re, Dulux, ATP/WTA, PTSB. Mentored 10+ junior and mid-designers—several now senior.
External sellers generated 66% of UK revenue, but the company had zero visibility into their activity until a merchant was already registered. 15-day activation had dropped from 62% to 48% in four months. 50% of sellers churned within their first three months. A previous CRM had failed because it demanded too much data upfront.
The brief said "build lead capture." The real problem was bigger: nobody had agreed on what a lead actually was.
I kept asking: "What is a deal? What is a lead? When does one become the other?" Engineering had built "leads" that behaved like deals. Product used terms interchangeably. The company's existing CRM had specific definitions nobody followed. Everyone was having conversations about the same thing using different words.
The resolution: what engineers had been calling a "lead" was actually a deal. A lead is a contact identity. A deal is a sales attempt. This single clarification restructured the backend data model and aligned three teams around a shared language.
300+ field agents needed to log opportunities on-site with merchants. But compliance required comprehensive data. These goals seemed incompatible—until I separated creation from enrichment.
I designed a progressive disclosure system: create a deal with just a name in 10 seconds. Enrich with contact details, offers, and compliance data later. Deduplication only triggers when a unique identifier is added—not at creation. The trade-off: accepting incomplete records temporarily. But field agents could now capture opportunities in the moment, and completion rates improved because the initial friction was gone.
Early prototypes tested multi-method capture: photo of a business card, voice input, manual search. Through 17 iterations I stripped the flow down to what field agents actually needed in the moment—while designing the system to handle complexity (multiple offers per deal, deal stage transitions, conflict resolution) without exposing it upfront.
The principle: agents always create a deal first. Identity comes later. This meant the UI could be radically simple at the point of capture, with depth available on demand.
The initial scope included AI data override functionality for handling automated capture edge cases. I questioned the actual frequency and impact. The result: weeks of engineering work deferred from V1, faster launch, no sacrifice to core value.
Stakeholders wanted new features—live scores, more stats, social sharing. The assumption was that the app was missing functionality. I synthesised 10,000+ app store reviews and found something different.
Users weren't asking for more. They were frustrated that basic features didn't work reliably. Crashes during live matches. Scores that didn't update. Notifications that arrived late. The problem wasn't missing features—it was broken trust.
Instead of "add more features," I proposed "rebuild trust through reliability." This changed everything: stakeholder priorities, sprint planning, success metrics. We shifted from feature count to stability metrics, from "what can we add" to "what must work flawlessly."
The trade-off was real: we deprioritised social sharing, advanced stats, and personalization features that competitors had. But a reliable app with fewer features would outperform a feature-rich app that crashed during Wimbledon finals. Stakeholders accepted this once they saw the review data.
This was a joint venture between two organisations with competing brand interests. Every design decision had political implications. Who gets top billing? Whose visual language dominates? How do we handle editorial content from both?
I established decision frameworks and content strategy for joint editorial workflow. The design system I created with React/Tailwind foundations established a unified visual language that both brands could own—neither dominant, both represented.
A junior designer joined their first enterprise project during this engagement. I established feedback cadence and design critique practices, guiding them through the ambiguity of multi-stakeholder work. They delivered production-ready components by project end.
The deliverables—wireframes, prototypes, component library, testing strategy—were solid. But the real value was the reframe. The rebuild launched with 40% fewer features than originally scoped, focusing on live scores, match schedules, and notifications that actually worked.
By investing in understanding the actual user problem (broken trust) rather than the assumed problem (missing features), we set the rebuild on a foundation that could succeed. The design system I created now serves as the foundation for both brands' mobile experiences.
The audit revealed something unexpected: the three previous designers hadn't disagreed—they'd never talked. Each had built their own patterns in isolation. The result was 47 button variants, 12 colour palettes, and zero documentation.
I interviewed customers and couriers in their actual environments—office desks, delivery vans, warehouse floors. The booking platform users wanted speed and clarity. The couriers needed glanceability and one-thumb operation. Different contexts, different needs, but both suffering from the same inconsistency.
I needed to create consistency across two very different platforms—a web booking system for enterprise customers and a native mobile app for couriers in the field. The constraint: I was the only designer, and both needed to ship.
I chose Atomic Design because it let me build once and compose infinitely—tokens and atoms could be shared across platforms while molecules and organisms adapted to each context. The trade-off was upfront investment: the first month felt slow as I built foundations instead of features. But by month three, I was shipping twice as fast as before.
The result: 47% boost in development efficiency and visual consistency across platforms serving 10K+ enterprise customers and 10K+ couriers.
In a lean 3-person Product team, strategic work wasn't optional—I stepped into it. I drove product strategy as a peer with CEO and CTO, orchestrated research across 5 teams and 3 dev squads, and delivered 80% on-time launches across 10+ features.
I also engineered a compliance solution protecting the company from legal exposure while expanding fleet capabilities, and implemented AI automation in Customer Service that reduced support volume while maintaining quality.
The most effective design systems include a shared vision between design and engineering, governance processes for reviewing new variants, a joint roadmap of prioritised updates, and documentation that extends past Figma components.
Implementing a new design is challenging because users are accustomed to old patterns. My approach: focus on improving usability over time while providing clear onboarding to help users navigate changes.
The single-user review system created an artificial ceiling on how fast enterprises could extract intelligence from critical documents. Every hour of delay meant delayed contracts, delayed decisions, delayed revenue.
Stakeholders initially wanted faster individual processing. I reframed the problem: What if document review wasn't an individual task but a collaborative intelligence system?
Through user research with financial services and legal teams, I uncovered that the bottleneck wasn't technical—it was organisational. Subject matter experts were gatekeepers, not collaborators. Documents queued in inboxes while decisions waited.
I designed three interconnected systems: Team-Based Document Pools for smart allocation based on complexity and expertise. Parallel Review Workflows enabling simultaneous processing with real-time status updates. And a Conflict Resolution System for handling overlapping edits elegantly.
The trade-off: parallel workflows introduced coordination overhead. Teams needed new rituals—handoff protocols, progress visibility, conflict resolution norms. I designed for this by making status visible at every level, so coordination happened through the interface rather than through meetings.
When the team restructured, I stepped into a consultancy leadership role—leading design across 6 engineering squads while directly mentoring 2 designers through project delivery. Managing 4 concurrent feature initiatives forced me to build systems for quality at scale, not just maintain it personally.
Early prototypes overwhelmed users. By revealing functionality based on context and role, the final design achieved both power and simplicity. Technical solutions must support organisational needs, not force new behaviours.
The stated problem: "We need a better booking system."
The real problem: The manual process was actively limiting how many campaigns could be processed, creating an artificial ceiling on ad revenue. Sales teams spent 70% of their time on administrative tasks instead of relationship building.
The stakes: In a market where streaming services threatened traditional TV advertising, Channel 4 needed to differentiate through frictionless agency experiences—or lose ground.
I conducted deep discovery interviews with agency representatives and internal teams. The surprising insight: users were attached to spreadsheets despite their limitations. The transition from manual to digital required psychological safety, not just better tools.
By incorporating familiar patterns and providing clear fallback options, I created a psychological safety net that encouraged exploration. External agencies could now allocate TV commercials independently, access real-time program metrics, and make smarter placement decisions.
The trade-off: I prioritised adoption over feature completeness. The first release didn't have every capability the old spreadsheet system had. But users who trusted the new system enough to try it became advocates—and their feedback shaped what we built next. Adoption-first beat feature-parity.
I redesigned the British Library website with a comprehensive WCAG-compliant design system, cutting navigation paths by 45% and increasing researcher satisfaction from 42% to 87%. This project taught me that accessibility isn't a constraint—it's a design driver that improves experiences for everyone.
Multiple departments with competing priorities and success metrics. I developed a structured workshop approach that visualised tradeoffs, building consensus around core user needs while acknowledging—and making visible—the business constraints each team operated under. This approach became a template for subsequent cross-functional projects.