AI fluency boils down to reframing business bottlenecks as prediction problems
sanderssays · x · 2026-10-20
Sanders argues the foundation of AI fluency is reframing traditional business problems — think bottlenecks — into prediction problems that AI can address. The culmination is knowing exactly when a workflow step calls for purely human, augmented human, or purely AI effort. An accompanying graphic lists four markers of fluency: reframing problems as prediction problems, giving agents durable instructions, verifying AI work, and knowing when to route to AI vs. humans.
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