When AI becomes infrastructure rather than novelty, what does education actually become? This collection features 12 educators and researchers examining teaching and learning in a post-AI world.

Through three sections-Reconceptualizing Foundations, Necessary Resistance, and Proof of Concept-contributors explore both AI's transformative potential and essential human elements that must be preserved. What distinguishes this work is its refusal to resolve tensions: it honors both the promise of personalized learning at scale and the irreplaceable value of productive struggle and human presence.

Readers find frameworks for curriculum design when content becomes commodity, warnings about over-optimization destroying purpose, examination of psychological risks in extended AI interaction, and working models from composition classrooms, graduate seminars, and civic learning systems.

This serves individual educators seeking practical approaches, administrators designing institutional responses, and policymakers ready to move beyond "how do we handle AI?" toward "what does education become when AI just is?" The diverse voices and deliberately disparate styles create a discussion-in-process rather than a definitive roadmap-exactly what this moment of transformation requires.