Beyond Scaling II: The Future-Transition Field / Runtime Transition Coordinates for AGI/ASI-Relevant Systems

Scaling has expanded what AI systems can do, but capability alone does not define the next safety bottleneck. As AI systems become more agentic, recursive, collective, and operationally embedded, their significance increasingly lies in runtime transitions that may begin to reshape observation, correction, and evidence conditions before outcomes are explicit or fully committed. This paper introduces the Future-Transition Field, a coupled abstraction for studying runtime transitions in AGI/ASI-relevant systems. It proposes the Precursor Condition: a minimum condition for intelligence beyond human level is the capacity to handle weak, partial, and context-dependent indications associated with consequential transitions before outcomes become visible or committed. The public runtime transition object is represented as X_t = (Ω_t, F_t, E_t), coupling observation context, future-condition structure, and evidence-validity structure. Existing runtime-safety methods are interpreted as partial views of this broader transition object. The broader mathematical framework underlying this public abstraction has also been subjected to a pre-declared internal adversarial falsification program across heterogeneous transition conditions. No irreducible counterexample was identified within the defined campaign. This does not constitute proof of universal validity. This publication intentionally remains at the theoretical, conceptual, and observational level. Operational realization and implementation-level details are outside its public scope.