Generated layouts arrive with confident typography and convincing spacing. They also arrive with inaccessible contrast, invented data patterns, and interaction models that ignore domain constraints. Teams under deadline pressure ship them anyway.
We define human-in-the-loop checkpoints for every AI-assisted design workflow: problem frame approval, research grounding, component compliance review, accessibility audit, content accuracy sign-off. No checkpoint, no ship.
Component systems as guardrails
AI output must map to an existing design system or explicitly flag deviations for review. Ungoverned generation creates design debt faster than any manual shortcut because volume masks inconsistency.
We train prompts and workflows against token libraries, not against generic internet UI — reducing plausible-but-wrong patterns before human review begins.
Accountability stays human
When a user is harmed by confusing consent flow, misleading copy, or inaccessible control, the organisation is accountable — not the model. Design is a political act; delegating values to automation without review is still a choice.
Our AI practice exists to amplify practitioner judgment across software, space, and brand — not to replace the responsibility that comes with shaping how people think, decide, and act.
The model suggests. Humans decide. Organisations answer for the outcome.