voice

The user is driving. Every design choice follows from that, and candidates who sketch a chat screen fail the question in the first minute.

A principal-level design and strategy question. Every default assumption (literacy, a good phone, fast data, English, a credit card) fails. The answer has to pick a job worth solving and an economic model that survives.

Shopkeepers want to know where their money is, in their language, without opening a dashboard. Start with answers that need no permission, add one-tap confirmed actions, and keep refunds and credit behind explicit approval.

Speaking is the skill learners avoid and value most. Design short, scenario-based calls at the learner's level with one correction per turn, and move it into the main paid plan once the cost per minute allows.

Translation is the smallest part of multilingual AI UX. The interviewer wants script choice, code-mixing, voice, cultural norms, and honest handling of languages where quality is weaker.

Voice adds two models and a much tighter latency budget to a text assistant. The interviewer wants the pipeline, the turn-taking problem, and the failure modes that text products never face.

Design task evidence, privacy controls and a separate diagnostic path without pretending that minimal telemetry proves semantic correctness.

Prototypes tested in English hide most of what goes wrong for users in other languages. The interviewer wants a prototype cycle that tests real speech and text from target users, with native evaluation.