Turn AI-fast prototypes into a scalable, on-brand system.

Anyone can generate a working screen now. Keeping a hundred of them consistent, accessible and on-brand is the hard part. I take raw AI output and sharpen it into a real design system — tokens, components and standards — and put AI to work inside the process to get there faster.

“It runs — but it won’t scale, and it’s off-brand.”

AI gets you to a working screen in minutes. It does not give you a system. I sharpen those outputs into consistent, reusable components — and use AI inside the work to move faster, while the judgment on what is right, accessible and on-brand stays human.

AI first, UX right after

The order is deliberate. AI produces working screens faster than any process can; the design work is what comes next, not what comes before.

01

Systematize

Let AI generate quickly, then inventory what came out — every spacing, every shade, every button variant — and agree the tokens and the one true version of each component.

02

Build

Rebuild the generated output against the system, with contrast, focus order and keyboard operation designed in rather than audited afterwards.

03

Scale

Hand over documented components in the framework your team uses, together with the rules that keep the drift from returning the week after.

01.Systematize

We start from what AI and your team already produced. I audit the screens, surface every inconsistency — the fourteen shades of grey, the five button styles — and define the foundation underneath: design tokens, a component inventory and the patterns that repeat. AI helps extract and cluster; I decide what is right.

UI & output auditDesign tokensComponent inventoryAI-assisted extraction
SCATTERED OUTPUTsystematizeTOKENS & COMPONENTSCOLORBUTTONRADIUS / SPACING

02.Build

Then the system gets built for real: a Figma library and matching coded components, every state covered — default, hover, focus, disabled, error — responsive and accessible to WCAG. AI accelerates the boilerplate and the variants; I make sure each one is correct, tokenised and on-brand.

Figma libraryCoded componentsStates & responsiveAccessibility (WCAG)
ONE COMPONENT, EVERY STATEDefaultHoverFocusDisabledBOUND TO TOKENScolor/brand/primaryradius/pillspace/inset/mdAccessible by defaultContrast, focus states and hit areas pass WCAG AA

03.Scale

Finally the system goes out into the product. Screens get built from the library — by your team and by AI — and they stay consistent because they draw from one source. You get documentation, hand-off and light governance so the brand holds at ten screens or a thousand.

Handoff & docsGovernanceBrand consistency
ONE LIBRARY → MANY SCREENSSYSTEMAI OUTPUTgenerated faston-brandConsistent at scaleDocs, hand-off and governance keep every screen on-brand

A system your team — and your AI — can build on

AI makes screens cheap. This makes them coherent. You get a design system that keeps every screen consistent, accessible and on-brand, however fast they are produced.

Outcome

  • A single source of truth: tokens and components
  • AI output refined to production quality
  • Consistent, accessible, on-brand UI
  • Faster, cheaper screens that stay coherent

Perfect for

  • Teams shipping fast with AI but drifting off-brand
  • Products that outgrew their first prototype
  • Founders who need design to scale without a big team

Type

Project or ongoing retainer

Who this is for

This is for teams that can already produce screens quickly — and are paying for it in inconsistency, rework and accessibility debt.

Team shipping with AI

AI gets you to a screen fast, and the screens do not match

Every generated view invents its own spacing, its own button and its own shade of the brand colour. The speed you gained comes back as cleanup.

You get tokens and components the generated output has to conform to.

Multi-product company

Your products have drifted apart

Two or three teams, three interpretations of the same brand. Every new feature widens the gap, and nobody owns the difference.

You get one system all of them build from.

Development team

You can build it, but nobody decides how it should look

Developers making design decisions under time pressure, and accessibility discovered during the audit rather than during the build.

You get a documented component library with WCAG built in.

Not sure this is the right one?

Questions people ask before starting

What is design engineering?

The work between a design and a working interface: turning design decisions into tokens, components and documented rules that developers build from. It is design expressed in the material the product is actually made of, rather than in a picture of it.

How do I build a design system?

Start from what you already ship, not from a blank file. Inventory the existing screens, find where the same thing is done five different ways, agree on one version of each, and express it as tokens and components. A system designed before the product exists tends to describe a product nobody went on to build.

Can AI build our design system?

AI is fast at producing components and slow at deciding which ones should exist. It will cheerfully generate a fourth button variant rather than reuse the third. With a defined token set and human review it removes most of the repetitive work; without one it multiplies exactly the inconsistency you were trying to remove.

How do you hand over to developers?

As components with named tokens, documented states and accessibility notes, in the framework your team already uses — I have handed over to Angular and Flutter teams. The handover says what each component is for and when not to use it, because that is what prevents the next variant from appearing.

Do you cover accessibility?

Yes, built into the components rather than audited afterwards. Contrast, focus order, keyboard operation and labelling are decided when a component is defined, following WCAG 2.1 AA and, for public-sector work, BITV.

Ready to make speed hold together?

A free 30-minute call. No pitch, no pressure — just an honest look at your product, your system and where design engineering would pay off.