AI made design output almost free. The hard part is judgment — knowing what's actually good, what to fix, and what's ready to ship. ADL is the operating system that gets AI-assisted design to production quality.
AI can generate endless possibilities. But AI cannot decide which solves the real problem. Which fits your users. Which should ship.
The space between AI output and what deserves to exist is
the Judgment Gap.
ADL is the operating system that closes it — turning unlimited AI output into decisions worth shipping.
A practical system of frameworks, workflows, and tools to help designers think, create, and lead with AI. Twenty chapters of thinking, anchored by a collection of reusable frameworks you can bring straight into real product work.
Five tools you’ll put to work — and one workflow that connects them.
The four moments every AI-augmented project moves through — with the designer, not the model, at the centre of the decision.
Catch weak AI-assisted work before it ships. Score five layers — problem, UX, design system, accessibility, decision — and get a clear ship / iterate / rethink call.
Generic AI output starts with generic input. Brief AI across five contexts — product, user, system, decision, output — so it reasons from your reality instead of its training average.
AI multiplies screens; systems make them last. Turn scattered output into reusable patterns, principles, and standards your whole team can build on.
Stop guessing at prompts. Six structured inputs — context, role, goal, constraints, output, quality — so AI works from your direction, not its assumptions.
The frameworks are free.
The thinking that connects them isn’t.
The AI-Augmented Designer Toolkit — the operating model, five framework Field Guides, the field notes, and the philosophy that turns five tools into one practice.
Get ADL·001 Toolkit —Five editable tools on Figma Community. Take them, use them, share them.
Explore Free Resources →Built from real product work — not theory.
Every framework was pressure-tested inside live products — enterprise design systems, AI product workflows, and the review processes product teams use to decide what ships. The playbook documents each as a Field Note: the real situation, the decision, and the system that came out of it.
Keeping components, tokens, and patterns consistent when AI multiplies output across dozens of contributors — and why speed was never the real bottleneck.
Deciding where automation helps and where human judgment has to stay — designing the collaboration model, not just the feature.
Turning ad-hoc critique into a repeatable review that scores AI-assisted work and produces a defensible ship / iterate / rethink call.
Written for the people who direct product design — not those chasing prompts.
Trade one-screen-at-a-time habits for a repeatable operating loop — frame, explore, evaluate, execute — so AI multiplies your options while your judgement still owns the outcome.
Give your team review frameworks and a maturity model that turn ad-hoc prompting into a consistent, reviewable practice — and a way to assess where the team really stands.
Methods for putting AI on top of your system instead of around it — keeping components, patterns, and constraints intact so speed never comes at the cost of consistency.
Where ADL earns its place in real product work.
Concrete moments where AI hands you output and you still have to make the call. Each one maps to a framework inside the toolkit.
Score AI-assisted work across five layers — problem, UX, design system, accessibility, decision — and get a clear ship / iterate / rethink call before it reaches a PR.
Run the flow through frame → explore → evaluate → execute so the critique is structured, not vibes — and the weak step becomes obvious to everyone in the room.
Pressure-test shallow AI logic against your patterns, principles, and constraints — turning “looks plausible” into something that actually holds up.
Walk into the review with a scored rationale: why this ships, what you traded off, what you’d revisit. Replace opinion with evidence.
Brief AI across six structured inputs and five contexts so it reasons from your product reality — not its training average.
Keep AI on top of your system instead of around it — so multiplied output still inherits your components, tokens, and rules.
Prompt packs vs ADL.
Questions designers ask.
No. ADL teaches the thinking system behind effective AI collaboration. Prompts expire with every model release — the operating model doesn’t.
The free frameworks give you the tools. The toolkit teaches you the operating system behind them — the playbook, five Field Guides, field notes from real product work, and every future update.
Product Designers, UX Designers, Design Leads, and teams adapting to AI — anyone whose job is shifting from producing screens to deciding what ships.
No. Your purchase includes every update to ADL·001 — the playbook, the five Field Guides, and the frameworks, as they evolve. Future volumes in the Design Intelligence Series are separate releases.
A growing library of frameworks, workflows, and systems for the next era of digital product design.
Twenty chapters. Five frameworks. One operating system
for closing the Judgment Gap.
Buy once — every update to this volume included.