We explore the growing tension between systems that promise certainty and the probabilistic tools that increasingly define our work, questioning whether we can still design for control when AI outputs are merely signals. We examine Pratik Joglekar’s warning against treating predictions as policy, Stephen Patterson’s insight that trust lives in visible micro-moments, and the stark reality that academic rigor doesn’t prepare us for industry friction. This episode challenges us to rethink how we assess readiness, manage burnout, and own the uncertainty that arises when prototypes meet production.
