Private AI
Bringing AI into private chats without breaking user trust.
Senior Design Director
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2024–2026
Launched the first privacy-preserving AI features on WhatsApp (message summaries, writing help, and Incognito Chat), built on Private Processing, with the architecture published publicly.
Problem
WhatsApp's promise is privacy, enforced by encryption: people trust it because no one, including Meta, can read their messages. AI features that process message content need exactly the access encryption denies, so AI and privacy seemed mutually exclusive. Trusted Execution Environments offered a partial technical path, but the harder problem was perception: people see 'AI' and 'privacy' as contradictory. The tension had to be resolved in the experience, not just the architecture.
Approach
Private Processing was the architecture: AI runs in a secure environment that even Meta can't access, so it can use message content without anyone, including Meta, reading it.
Features were opt-in and off by default, and Incognito Chat is ephemeral, so the user stays in control. The architecture was published and independently audited, so the privacy claim could be verified, not just asserted.
Process
Strategy definition
Defined which AI experiences could work within TEE constraints, what capabilities needed building, and how to sequence launches. Presented the strategy in multiple CEO reviews, securing support to build Private Processing prototypes on the strength of the product vision.
First launches (2025)
Shipped unread-message summaries and writing help, both process data in a TEE, return a result, and retain nothing. The engineering architecture was published publicly, making transparency part of the product.
Private AI system
Created the visual design language for Private Processing, led naming and positioning, and defined the design criteria for what qualifies as ‘private’: no data retention, TEE processing, user-initiated, transparent disclosure. Aligned the roadmap toward the 2026 launch.
Incognito Chat (2026)
Incognito Chat: a fully private way to chat with AI on TEE infrastructure. Messages are processed but not stored, no training on conversation content, with audit mechanisms for verification.
Outcome
Users found the privacy framing reassuring rather than alarming. The launch was covered by global press outlets, and the work helped establish WhatsApp’s approach to privacy-preserving AI.
Incognito chat with Meta AI
Incognito chat with Meta AI
Private writing help
Private message summaries
Lessons
How a capability is presented matters as much as the capability. Processing message content reads as invasive or helpful depending on framing, so positioning and transparency were as important as the product work.