Design AI features for WhatsApp (support, safety, and productivity).

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ANSWER MODE

WRITTEN ANSWER

### Signal to interviewer

I can design messaging AI that delivers utility while respecting safety and privacy constraints at scale.

### Clarify

I would clarify regional usage patterns, privacy expectations, business messaging policies, and high-risk abuse vectors.

### Approach

Use a utility triangle: support automation with escalation, safety risk detection with proportional intervention, and productivity assist for everyday conversations.

### Metrics & instrumentation

Primary metric: first-contact support resolution in messaging workflows. Secondary metrics: warning effectiveness, summary usage, and translation satisfaction. Guardrails: false abuse flags, privacy complaint volume, and delayed urgent response incidents.

### Tradeoffs

Stronger safety models reduce fraud but can over-interrupt legitimate chats. Rich productivity features help users but can increase perception of surveillance if not transparent.

### Risks & mitigations

Risk: scam adaptation; mitigate with continuously updated detection. Risk: mistrust in interventions; mitigate with clear rationale and controls. Risk: poor escalation experience; mitigate with context-preserving handoff.

### Example

In merchant support chats, AI handles return-status queries, flags suspicious payment links, and summarizes unresolved issues before a human agent joins.

### 90-second version

Design WhatsApp AI around support, safety, and productivity together. Measure resolved outcomes, apply risk-tiered protections, and keep privacy trust central to every feature decision.

FOLLOW-UPS

Clarification

What safety interventions are acceptable without violating user trust?
Which support journeys should be fully automated first?

Depth

How would you deploy scam detection while preserving end-user privacy?
What escalation contract ensures human handoff quality in business chats?

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