AI-NATIVE
I design the surfaces where people work with AI. Copilots, AI receptionists, automated workflows. At AutoLeap I led an AI repair-order flow and AI Receptionist that helped drive +$4M in enterprise revenue.
I design AI-native products grounded in research. Every claim is evidence-chained, confidence-scored, and holds up under scrutiny. I've taken 0→1 platforms to enterprise scale at AutoLeap, Careem, and EY, then shipped them to prod.
I design the surfaces where people work with AI. Copilots, AI receptionists, automated workflows. At AutoLeap I led an AI repair-order flow and AI Receptionist that helped drive +$4M in enterprise revenue.
0→1 by default. I built Articos, a protocol-driven AI research platform, from scratch. It validated at 86% theme recall and 7.5× the accuracy of raw prompting.
Evidence over opinion. I'm grounded in JTBD / Outcome-Driven Innovation at Strategyn, with published research in IEEE & SSRN. I make findings auditable and defensible for stakeholders.
I built a protocol-driven AI research platform that produces evidence-chained reports with confidence scoring. It is not a chat wrapper. Hypothesis-blind personas reduce self-fulfilling answers, and every theme links to quotes, questions and refutation counts.
As Principal Product Designer I led four back-to-back initiatives: a Digital Vehicle Inspection overhaul, a visual Kanban work-management system, an AI Receptionist for missed calls, and a "magical" AI repair-order generator that solved the blank-page problem for service advisors.
Careem (a vehicle-for-hire operator across 100+ cities, 15 countries) ran support on fragmented systems built for other roles. I used the PACT process: interviews, system mapping, sentiment and data-visualisation. From there I designed a unified agent experience and measured the lift, cutting issue-resolution time.
Design is most valuable when it's defensible.
I'm an AI-native product designer who treats research as infrastructure. I've shipped 0→1 AI products and scaled enterprise SaaS, but the throughline is the same. I turn ambiguous, high-stakes problems into interfaces, and into evidence, that teams can trust.
I work where product strategy, AI capability, and research rigor meet. Then I ship it to prod.
Every claim traces back to a source. Confidence is scored, not asserted.
From blank-page products to enterprise rollouts across web, desktop and mobile.
Capability people can trust, audit, and defend internally.
Prototypes that become products, not decks that become slides.
"Ship evidence, not opinions. Make the work auditable, and it becomes impossible to argue with."