The whitepaper maps Sutskever's AI research themes (eval-reality gap, continual learning, generalization) to holonic capabilities. Concretely: if an agent completes a coding task and learns something about a codebase, what's the exact sequence of holon operations that "saves" that learning so future agents can reuse it — and how do you prevent the shared store from accumulating noise?