Meta Design Director Alex Cornell: AI Agents Should Be Designed for Conversations, Not Interactions

In the How I AI podcast, Meta Design Director Alex Cornell articulated the core interface philosophy behind Muse, an AI agent he leads designing. His guiding question was, "How would this work if you were talking to another human?" This principle drove the removal of traditional message bubbles and the placement of the agent at the top of the screen, rather than inside a standard chat window. Cornell argues that AI agents should be designed for conversations with people, not interactions with software.

To accommodate users with varying technical expertise, Muse employs "progressive disclosure." The same activity is represented at three levels: a simple emoji for casual users, a task list for those wanting more detail, and raw logs for engineers. This ensures each person gets the transparency they need without adding clutter for everyone else. Cornell identifies this as one of the most useful principles in AI product design.

Regarding the popular feature of "visible chain-of-thought" (displaying reasoning steps), Cornell offers a counter-intuitive view: it is often a workaround for latency, not a valuable feature. Many AI products display thinking steps to reassure users while a slow model works. However, Muse is fast enough to operate quietly and simply deliver the result. This suggests that when an agent can provide answers quickly, it does not need to perform its thinking process.

For generative UI, Muse adheres to the principle that "structure stays fixed and content changes." The avatar, feed items, and idea cards are deliberately designed static surfaces. Dynamic elements are limited to the agent's status emoji, personalized suggestions, and small animations, allowing the experience to feel alive without rebuilding the interface every session. Additionally, Muse's main chat is designed as a single persistent relationship, preserving continuous context, while side chats handle scoped tasks. Cornell believes the industry has not fully explored the value of this ongoing conversation model.