Hands on AI Product Design Leader
I combine AI product thinking with high craft design execution,
and lead by example.
A handful of projects I'm proudest of, picked to show range rather than a highlight reel of one kind of problem. Each one covers the constraint that shaped it, not just the pretty screen at the end.
Agentic Replatform
Replatforming a rigid stepper flow into a conversational agent interface, sheets of data that layer and peel back like paper on a desk, shipped to every customer and now core to the platform.
Read case study →
Team Leadership
Embedding designers in delivery squads so a government project could hit its immovable deadline, with usability testing restored and design work finally visible to delivery.
Read case study →Agent Interface
Replacing hand-built templates and manual post-processing with a conversational agent that works on a live template artifact, delivered before Black Friday.
Read case study →
Small tools I've built to chase a curiosity or scratch an itch, usually outside of any brief. They don't always go anywhere — but every one of them has taught me something I've carried back into the day job.
I had been thinking for a while about how light sources work and how they are applied in UI design.
For the most part depth is simulated with the use of shadows. I wanted to experiment if I could take that further by also applying highlights and colour gradients as if the objects were being lit from a single light source.
[Placeholder] One or two lines on what it does and why you built it.
Try it →[Placeholder] One or two lines on what it does and why you built it.
Try it →
A handful of habits I keep coming back to, from how I dig into a problem to how I hand the repetitive parts off to agents. None of them are about being clever — they're about noticing what matters, staying consistent, and making sure the people around me come out ahead too.
Before I sketch anything, I want to know who I'm actually designing for — what they're dealing with, what the business needs, and what's getting in the way. Slowing down here saves everyone time later.
Problems rarely announce themselves. I notice them early, and put effort where it counts.
Finding the right answer takes real effort — understanding the problem properly, not settling for the first idea. But that doesn't mean it should take weeks. I get there fast, ship it, and let real use tell me what I got wrong.
Somebody has to hold the messy, complicated reality of a system so the person using it doesn't have to. I don't mind that job — it's most of what design actually is.
I do my best thinking out loud, in a room with engineers and product people poking holes in it. The work gets better when more people care about it, not fewer.
Small inconsistencies don't feel like a big deal in the moment, but they add up into a product that feels like nobody's looking after it. I try to be the person who is.
The proudest moments in my career haven't been my own work — they've been watching someone I've mentored do something better than I could. That's the job, really.
I let agents do the repetitive grinding — the drafts, the variations, the busywork. What I bring is taste: knowing which of those ideas is actually good.
Design thinking extended with build and monitor stages, and feedback loops that pull learnings back to earlier stages instead of starting over. At every stage I set direction and make the calls — agents take on the repetitive grinding that used to eat the time in between.
Understand users, business context, and constraints, including where AI can genuinely help and where it can't.
Me I run the interviews and read between the lines only a human catches.
Agents Digest transcripts, tickets, and analytics into patterns I can sanity-check.
Frame the real problem, and identify where deterministic flows break down and agentic behaviour is the better fit.
Me I write the brief and draw the line between what's deterministic and what needs judgement.
Agents Draft problem statements and edge-case lists for me to argue with.
↩ Loops back to DiscoverExplore concepts across both interface and agent behaviour, not just screens, but how the system reasons and responds.
Me I set the concept direction and call which ideas earn a prototype.
Agents Fan out variations fast, so I'm critiquing options, not staring at a blank page.
Build clickable and agent-backed prototypes to test real interaction, not just visual design.
Me I design the interaction and decide what "good" looks like before it's built.
Agents Wire up working prototypes against real model calls, not Wizard-of-Oz screens.
↩ Loops back to IdeateValidate with real users and real model behaviour, refining acceptance and success criteria stage by stage.
Me I run the sessions and read what users don't say out loud.
Agents Log failure modes and flag where model behaviour drifts from the brief.
↩ Loops back to Ideate & DiscoverTurn validated prototypes into production-ready features, in close partnership with engineering.
Me I pair with engineering to protect the interaction and behaviour we validated.
Agents Handle the repetitive implementation grind — variations, edge cases, boilerplate.
Watch how it performs live, then feed what's learned back into earlier stages rather than starting over.
Me I watch the metrics that matter and decide what's worth acting on.
Agents Surface anomalies and usage patterns I'd otherwise miss.
↩ Loops back to Discover
Most recently, I’ve been Head of Design at an AI-native SaaS startup, going from 0-1 and defining how an agentic product moves and behaves. Before that, 15 years spanning multinational consultancies and large-scale government digital delivery. I work best where I’m setting the vision while staying close to the interaction and interface design craft.
May 2022, Present
Ocula Technologies
B2B SaaS startup providing AI-powered product data enrichment and content generation for large-scale e-commerce retailers including AO.com, House of Fraser, ASDA and M&S.
March 2017, May 2022
Kainos
Multinational digital consultancy specialising in government, healthcare and enterprise digital transformation. Led design across a 60-person design organisation, managing designers, researchers and service designers on multi-million pound contracts.
November 2014, March 2017
Sopra Steria
International IT consultancy serving local and regional government, healthcare, financial services and commercial sectors. Managed a team of UX designers and researchers across multiple concurrent projects.
January 2013, November 2014
Storm ID
Digital transformation consultancy based in Edinburgh, serving government, healthcare and commercial clients.