Research and feedback pile up faster
than anyone can synthesize them
Our process
A design process built around decisions
Every cycle moves a clear question to a buildable answer. AI accelerates the work around each decision; designers make every call. This page shows the full method
Built for teams outpacing their design capacity
The tools changed. The agency model did not
An AI-augmented design process is a workflow where senior designers use AI at every production stage — research synthesis, exploration, prototyping, and design-system upkeep.
AI accelerates production work; designers own judgment, quality, and every final decision.
What we solve
Where product design
slows down
Once a product is live, most delays don’t come from the design
itself. They come from the work around it
Teams commit to the first idea that works,
instead of the best of several
Prototypes take too long, so validation
happens after the build, not before
The design system drifts as new
features pile on
Handoff is incomplete, so engineering
stalls on open questions
Adding design capacity means months
of hiring or a bloated team
Decision-led, AI-accelerated
Four stages, one rule: AI accelerates the work around each decision — the decision stays human.
We start from the decision that matters: what are we improving, and how will we know it worked?
Designer defines the problem and the decision worth making.
- Research data
- User feedback
- Analytics data
- Product context
We widen the search before we narrow it
Designer rejects weak directions and sharpens the strongest
- User flows
- Structures
- Concepts
- Alternatives
Promising ideas become clickable early — before engineering effort makes change expensive
Designer shapes the experience and decides what is ready to test
- States
- Variations
- Content
- Prototypes
Approved work becomes reusable components, patterns, tokens, and documentation
Designer owns structure, quality, and what enters the system
- Components
- Tokens
- Patterns
- Documentation
THE AI WE USE
The AI behind every step, not every decision
AI is part of our production layer — not our approval chain. We use it where it removes repetitive effort, widens exploration, or processes large amounts of material quickly.
-
01
Research & synthesis
Large language models (e.g. ChatGPT, Claude) to digest interviews, support tickets, analytics, and competitor scans.
-
02
Exploration
Generative UI and visual tools (e.g. Figma AI, UX Pilot, Midjourney) to widen the range of directions.
-
03
Prototyping
AI prototyping and code generation (e.g. Figma Make, v0) to reach clickable states quickly.
-
04
Interface content
Language models to draft UI copy and empty, error, and edge-case states.
-
05
Design system
AI to generate and maintain component documentation, tokens, and patterns
Accountability
AI assists. People decide.
- Organize research
- Compare patterns
- Generate directions
- Draft content
- Accelerate prototyping
- Document decisions
- The problem
- Product judgment
- Visual quality
- User context
- The recommendation
- Final decisions
WORKING WITH US
Less waiting. Fewer
layers. Clearer decisions
Most design delays come from unclear ownership, long feedback chains, hidden work, and decisions that arrive too late. We remove those
DEFINITION OF DONE
A finished screen
is not a finished design
Before work is ready for engineering, we confirm that:
The primary user flow is complete
Key states and edge cases are covered
Interactions and behavior are clear
Interface content is included
Components and patterns are mapped
Responsive behavior is addressed
Engineering reviewed the proposed solution
Decisions and assumptions captured
OUTCOMES
The standards behind the work
New features and screens shipped faster
The design system stays consistent as you grow
Cleaner handoff and fewer engineering stalls
FAQ
What clients ask us most
What AI tools do you use?
A mix of language models for research synthesis and interface content, and generative UI and prototyping tools for exploration and speed. The exact stack adapts to each project — and every output is reviewed and approved by a senior designer.
How long does a typical design cycle take?
Days rather than weeks for most cycles: first directions early, validation before engineering planning. The exact pace depends on scope and how quickly your team can review and decide.
Does AI replace your designers?
No. AI supports the workflow; it never makes the call. Our designers own the problem, product and UX judgment, visual quality, and every final decision. AI explores; designers decide. The tool creates leverage — the team keeps accountability.
Does AI make the design decisions?
No. AI widens the options and handles repetitive production work. Our designers own direction, judgment, quality, and every final call.
How is this faster than a traditional process?
AI removes the slow parts — digesting research, producing variations, documenting systems — so senior designers spend their time on decisions, not production.
What does a dev-ready handoff include?
Complete primary flows, key states and edge cases, interaction behavior, interface content, mapped components, responsive rules where relevant — reviewed with engineering, with open decisions documented.
What do you need from our team?
A decision owner who can confirm direction, access to product context (roadmap, research, analytics), fast specific feedback, and an engineering counterpart for feasibility checks.
Bring us the bottleneck
Show us where your roadmap is slowing down. We’ll recommend the smallest useful engagement to get it moving again — and tell you where AI helps and where it doesn’t.
Start a project