Can use micro-interaction accessibility review with a defined task, suitable inputs, and a basic validation check.
augmented skill · Stage 06
Micro-interaction accessibility review
Micro-interaction accessibility review is the discipline of catching AI-default carousels/auto-advance that create friction. It helps a designer translate intent into coherent interaction, visual language, motion, and edge states while keeping the final judgment traceable and human-owned.
Why it matters
This skill supports reliable work in Experience Crafting and prevents speed from being mistaken for quality.
Stage outcome
Apply behavior, motion, and visual language to the architected structure, the concept becomes a specific, branded, functioning experience
What good looks like
01
Frames micro-interaction accessibility review against a clear goal, relevant evidence, and the stage quality gate.
02
Directs AI with scoped inputs, reviews uncertainty, and redirects weak or unsupported output.
03
Documents the decision, trade-off, correction, or override so another designer can follow the reasoning.
Checkpoint application
Apply this skill before the Stage 06 gate is approved. The accountable designer must be able to explain how it changed the work, what evidence was considered, and why the result is safe to advance.
Common failure patterns
- Shipping AI-default craft, happy-path-only states, or interactions that weaken brand and accessibility.
- Accepting fluent or high-confidence output without testing its evidence, assumptions, exclusions, and downstream effects.
- Recording the final artefact while omitting the rejected option, correction, trade-off, or override that explains the decision.
Five-minute practice
Use it on the work you already have.
Take one current experience crafting artifact. Apply micro-interaction accessibility review for five minutes, then record one AI contribution, one human correction, and the evidence that justified the final decision.
Evidence of capability
- A reviewed interaction flow, visual system application, prototype, or edge-state set showing the skill in use.
- A short rationale linking the decision to evidence, risk, and intended outcome.
- An example of an AI suggestion that was corrected, rejected, or deliberately accepted.
Leadership assessment questions
01
Can the designer demonstrate micro-interaction accessibility review on a real experience crafting decision?
02
What observable evidence distinguishes competent performance from confident explanation?
03
Which anchor skill depends on this capability, and how would a gap surface in delivery?
Maturity ladder
Can diagnose weak output, redirect the work, combine sources, and explain the resulting trade-off.
Can decide when not to delegate, own the human checkpoint, and remain accountable for the outcome.
Backlinks and relationships