From first conversation to something live in the wild — embedded in the team, working through ambiguity alongside engineers and stakeholders. AI accelerates the parts that should be fast, never the parts that require judgment.
Process
I run two methodologies back to back. Double Diamond is the discipline of finding the right problem before building anything — diverge to explore, converge to decide, twice. But a validated concept that never ships is worth nothing. So once the problem is clear, I switch to the Snowball Sprint: short cycles that ship, prove, and compound value before skepticism sets in. They don't compete — they operate at different altitudes, and they're strongest run in sequence.
Use Double Diamond once to find the right beachhead. Then Snowball Sprint to own it. Skip the Diamond and you ship a flawless solution to the wrong problem; skip the Sprint and the validated concept never leaves the page.
Problem-centric. Most teams jump to solutions before understanding the problem deeply enough. The discipline is slowing down to look wider before narrowing.
About being right.
Momentum-centric. Most AI programs die not from bad ideas but from stalled execution and eroding trust. The discipline is speeding up the proof cycle before skepticism sets in.
About staying alive long enough to get better.
Where they agree
The Diamond surfaces them through research; the Sprint surfaces them through shipping. Either way, they get tested.
Neither bets everything on a single big-bang waterfall delivery. Both improve through repeated, deliberate passes.
Both keep a human in the loop at the key inflection points. AI accelerates the work — it never makes the call.
When to lead with which
Skills
Thirty years in digital, the last decade focused on product design leadership across fintech, SaaS and regulated environments — from discovery and research through to shipped, production-ready products.
How I build and lead design teams — establishing the culture, process and operating model that lets designers do their best work.
Experience
Approach
How I connect design decisions to business outcomes — from shaping roadmaps and defining success through to facilitating discovery and keeping scope honest.
The sectors and product types I know deeply enough that domain expertise replaces research time — I understand the constraints before the brief lands.
How I close the gap between what's designed and what ships — using AI-assisted pipelines that take Figma layouts to production components without fidelity loss.
Qualifications
Process
How I work inside product and engineering teams — from sprint planning and backlog refinement through to stakeholder reviews and regulated release cycles.
The full stack I use to design, build and ship — from component libraries and design systems through to deployment pipelines and production environments.
From early wireframes to polished, production-ready components. The tools I use to design, prototype and build at every fidelity.
Product design leadership across fintech, SaaS and regulated environments — from discovery through to shipped.
Designing AI-enabled products where the model is a first-class part of the experience.
