A Generative Education Architecture for Planetary-Scale Personalized Learning

This paper describes a generative education architecture integrating six interdependent dimensions — deep learner profile, data sovereignty, generative learning experience, federated knowledge graph, process-based competency evidence, and trustee governance — into a unified system. No dimension works without the others. The dependency graph forces integration. Every component technology exists in production. The original contribution is the demonstration that the pieces are architecturally interdependent and that their integration produces a system qualitatively different from any subset. The architecture enables an AI Mentor — constrained by a federated knowledge graph, informed by a lifelong learner profile, governed by a trustee structure, and cryptographically prevented from exposing its data — to generate the learning experience itself, for each individual, at near-zero marginal cost.