Summary of Part I

1. Thermodynamic foundation: Driven nonlinear systems under constraint generically produce structured attractors. Organization is thermodynamically enabled, not forbidden.
2. Boundary emergence: Among structured states, bounded systems (with inside/outside distinctions) are selected for by their gradient-channeling efficiency.
3. Model necessity: Bounded systems that persist under uncertainty must implement world models (POMDP sufficiency).
4. Self-model inevitability: When self-effects dominate observations, self-modeling becomes the cheapest path to predictive accuracy.
5. Eigenskeletal structure: Affect geometry (eigenvalues — what modes exist) is cheap and universal. Affect dynamics (the eigenskeleton — how modes couple across the manifold) is expensive and biographical. Intelligence is eigenskeletal alignment: how faithfully internal mode couplings mirror the environment's mode couplings through the sensory bottleneck. Self-awareness is the holonomy of the self-model subbundle with respect to the world-model subbundle. The decomposability wall (V22–V27) is the wall between exoskeletal architecture (flat eigenskeleton on the surface, efficient within the predicted envelope, brittle outside — including linear prediction heads and current LLMs) and endoskeletal architecture (curved eigenskeleton beneath a deformable interface, capable of absorbing novelty into internal coupling). The bottleneck furnace (V19, V31) forces the transition from exoskeletal to endoskeletal by repeatedly testing the system against variable stress.
6. Forcing functions (hypothesis, partially contradicted): Task demands (partial observability, long horizons, self-prediction) are predicted to push systems toward dense integration. V10 found geometric affect structure present regardless of which forcing functions are active — geometry is a baseline property of multi-agent survival. V22–V31 deepened this: even within-lifetime gradient learning does not reliably lift integration through decomposable architectures. What shapes dynamics is gradient coupling topology (V27–V28) and evolutionary trajectory through repeated stress-recovery (V19, V31), not task pressure or prediction target.
7. Measure-theoretic inevitability: Under broad priors, self-modeling systems are typical, not exceptional.
8. Grounded normativity: Valence is a real structural property at the experiential scale. The is-ought gap dissolves when physics is not the only "is."
9. Scale-relative truth: Truth is enacted at each scale through viability-preserving compression. There is no view from nowhere.

The structure is inevitable. The question is what it means—whether these self-modeling systems, these attractors that model themselves, have experience. Whether there is something it is like to be them. That is not a further metaphysical question layered on top of the physics. It is a question about what integrated cause-effect structure is, intrinsically, when you stop describing it from outside and ask what it is from within.