The full one-to-one experience, per person. Their own diagnostic and path, their own AI co-pilot as a guide, their own product carried from idea to a working build. Best when you want a few people taken deep and to return with greater capability.
FOR TEAMS · DESIGNING WITH AI
Turn your A teaminto an A+ team.
One shared way of working with AI, built by doing real product work.
Design is about delivering solutions to problems nobody else thought of, not drawing rectangles or following patterns, through communication, craft and judgement. Up to now, your team's bottleneck has been a lack of diverse skills and ever-closing timelines, often causing you to ship the first solution to a problem. AI changes that. It plugs the gaps in your team's capability and frees them to chase higher-value ideas they previously discarded. This course teaches your team to use AI to augment their skills and push their ideas further than ever before.
THE PROBLEM THIS SOLVES
Most AI training is passive and focused on tools. I focus on people and outcomes, so your team learns how to work differently and deliver better results together.
Your team has sat through webinars and read the threads. They've dabbled with AI, but that's not the same as using it in a team under pressure to deliver. I focus on how you can operationalise AI in your team's day-to-day.
What makes me an authority on AI within design? I've spent the last two years rebuilding how I work around AI on real products in startups and large orgs. With 30 years leading teams and delivering high-stakes products, I bring training that helps your team apply AI effectively.
HOW IT STARTS
A 1:1 diagnostic for every team member
Every person starts with the same diagnostic I run one-to-one. Each person comes away with a clear understanding of where they are, their AI maturity and what to focus on next. As a design leader, you come away with a map of where the whole team sits on the AI Native ladder, and where the effort will pay off most.
That map shapes the curriculum before we start.
TWO WAYS TO RUN IT
Individual seats, or a group cohort
The course adapted for the team. Shared live lectures, the curriculum aligned to your goal, and the team split into small squads that each build a real product across the programme. Best when you want the whole team to learn together and come away working more consistently.
- Diagnostic 1:1s for every person
- 1:1 check-ins through the build
- A private Slack channel, me in it throughout
- A shared cohort co-pilot recapping the group's progress (paid step-up)
You lose the per-person AI guide. You gain a team that learns together, holds each other to it, and comes out working the same way, with shared habits and clearer delivery.
WHAT WE FLEX
The curriculum bends to the team.
Sixteen lessons, five stages, but not every team needs every stop. We set the weighting based on the diagnostic map: heavier on skills and agents for one team, on concepting and design systems for another. The extended track comes in when it's your team's systems, rather than its craft, that are holding things up.
THE CURRICULUM
Sixteen lessons across five stages
Here's the whole route, before we weight it to your team. Some lessons are pure technique, learned on their own; others each squad applies straight to the product it's building.
Get AI ready
Foundations
Get AI working for youBy the end you'll know how these models actually work, you'll have one workspace where you and AI both read and write, and you'll know how to hand AI the context a design task actually needs. The groundwork, before we go near the design.
your free diagnostic, then three lessons
0
Your diagnostic (free)
A one-to-one where we find how you use AI now and where the gaps are, then plot your path through the course. You leave knowing your starting point.
1
AI technology foundations
Do you know how AI actually works? The foundational knowledge you need to use it as a creative tool: what it knows, why it makes things up, and when to reach for a lighter or heavier model.
2
Design workflows with MCP
MCP is the key to creative collaboration. You set up a human/AI design workspace and explore some neat ideas on how to work together in it.
3
Communicating context to AI
Established UX and product techniques for giving AI the right context in the right way, so it fully understands the design task at hand. You build a story map with Claude as a live collaborator on the board.
Explore
Concept
Design it with AIBy the end you'll have concepted an idea as a full design exploration, from static concepts through to interactive studies, and made AI design with your design system instead of reverting to its own defaults.
two lessons
4
Concept design with AI
Use Claude Design to concept multiple ideas through mini experiments, from static design concepts to interactive studies, learning how to break design down into a full design exploration.
5
Designing with a design system
How do you make sure AI is using your design system when it creates output? Setup and execution of working with an established design system.
Amplify
Specialise
Make AI work the way you doBy the end you'll have built skills and agents specific to product design, and you'll know how to judge what AI hands back rather than taking it on trust.
three lessons
6
Creating and using AI skills
Skills are a powerful way of making AI specialised. You build on what you already know and create skills specific to product design.
7
Creating and using AI agents
How to think about agents in a design context, and how to build ones that practically increase your output.
8
Evaluating AI output
AI doesn't always tell the truth, but how would you know? The best way to make sure it's accurately using your design system and your brand.
Prototype
Prototype
Make it real and testableBy the end you'll have taken your concepts through to an advanced prototype you can share and test with users, one that's indistinguishable from a real product and can act as your source of truth for design.
three lessons
9
Interactive prototyping level 1
Take your concept designs from experiments to a working prototype, with plenty of tips and tricks for building fast while reducing complexity and saving tokens along the way.
10
Dev studio setup
Create your own personal engineering team and workspace, ready for advanced prototyping.
11
Interactive prototyping level 2
A practical session building an advanced prototype you can share and test with users, indistinguishable from a real product and able to act as your source of truth for design.
Go further
Extended
Into the team, and into the buildBy the end you'll have rebuilt your own design process around AI, closed the gap between your design system and the code it ships as, and taken a prototype all the way to a working proof of concept.
five lessons
The extended track. Five deeper lessons for designers who want to go past the prototype, into the systems and the build. The diagnostic map decides whether they're part of your team's path.
12
Reinventing process with AI
Apply everything you've learned to build a human-led, AI-powered design process, balancing human judgement against AI automation.
13
Aligning design and code systems
Aligning systems between code and Figma, porting interface code back into Figma so the library reflects what's actually built.
14
Structuring Figma for AI
Organising files, components and naming so the library is legible to a model rather than only to a designer.
15
APIs, databases and more
Understanding the basics of technical architecture: how data is stored, how services talk to each other, and enough to make good calls about your own.
16
Turning your prototype into a PoC
A hands-on session building a working proof of concept, delegating real build tasks to Claude Code while keeping your judgement over what it produces.
Talk to me about your team
Each squad finishes with a real product, built and working.
WHAT THE TEAM WALKS AWAY WITH
A way of working, not a workshop memory
A way of working with AI
One the team keeps and builds on.
Real product from each squad
Built and working.
One shared operating model
So everyone briefs AI the same way and gets more consistent results.
The judgement to know when AI is wrong
The part no tool gives you.
TAUGHT BY SOMEONE WHO'S DONE THE JOB
I've spent 30 years designing and building products, in-house and on the tools, at Microsoft, Channel 4, Sainsbury's, NatWest and E.ON. Over the last two years, I've rebuilt the way I work with AI on real 0-to-1 products, so your team learns what I actually do from someone who is still doing it.
Microsoft
Channel 4
Sainsbury's
NatWest
E.ON
LET'S TALK
Tell me about your team.
Where they are with AI, what you want them building, and how many. I'll come back with a shape and a plan for the outcome you want.
A few teams at a time, so the support stays real.