AI-first products shift the focus from optimizing UI funnels to designing system capabilities that are contextual and non-deterministic.
The product is the entire reasoning system, including user intent, orchestration, the core model, memory, and action-taking tools.
Effective UX for AI relies on principles like clarity of capability, graceful failure, and user agency rather than traditional UI components.
Trust is built by showing the AI's reasoning, calibrating its confidence, and implementing human-in-the-loop approvals for high-stakes actions.
Products like GitHub Copilot, Notion AI, and Perplexity demonstrate successful patterns for ambient assistance, co-authoring, and transparent reasoning.
The future of AI product design involves shifting from designing flows and error states to designing goals and uncertainty states for proactive systems.
Jobs that call for the skills explored in this talk.