Accessibility in AI generation workflow
Your team keeps shipping AI-generated UI components that pass design review but fail accessibility audits weeks later (missing labels, no keyboard support, color-only state). Rather than fixing each one after the fact, you want to change how the team prompts and verifies. As a staff engineer, what would you put in place so accessibility is part of the generation loop, not a cleanup pass?
Implement
audit_component_accessibility(elements: list[str]) → list[str]Examples
in
[["button label=Save keyboard=yes contrast=700"]]out[]in
[["button keyboard=no contrast=320","div state=color"]]out["0:missing-name","0:no-keyboard","0:low-contrast","1:color-only-state"]in
[["link label=Docs keyboard=yes contrast=450"]]out[]What a strong answer looks like
Treat the AI’s output as a draft to verify, not an answer to trust. Name the specific flaw and the input that triggers it, say how you’d catch it (tests, edge cases, reading critically), and how you’d re-prompt or decompose to get it right.
0:00 of about 19 min
Vibe & agentic: describe the solution in plain language (or narrate it) and the coach grades your approach.
Which questions mattered is sealed until you submit. Telling you now would just be handing over the edge cases.
Run or narrate your approach, then ask the coach.