AI products are evolving from passive tools into adaptive partners that think with us, though many pilots fail because they don't successfully change user behavior.
A beehive serves as a model for designing AI, emphasizing distributed intelligence, simple rules, and local signals to create complex, adaptive behavior.
AI can interpret user actions like clicks, pauses, and drop-offs to detect friction and proactively suggest solutions, such as breaking large tasks into smaller subtasks.
Contextual signals like time of day, device, and calendar events allow AI to automatically adjust the product experience, such as enabling a focus mode after work hours.
By analyzing patterns in micro-decisions, AI can infer user preferences to automatically adjust layouts and default views for a more tailored experience.
Integrating external data signals, such as weather forecasts, enables AI to be resilient and proactively adapt plans, like rescheduling an outdoor meeting for rain.
High-profile failures from companies like Klarna and Air Canada show the risks of optimizing AI for speed over human relationships and trust.
The future of AI products relies on combining data with human empathy, using AI as a tool that complements irreplaceable human skills like creativity and relationship-building.
Jobs that call for the skills explored in this talk.