Summary

Thirty-five experiment versions across four substrates and fifty seeds at scale. Twelve numbered measurement experiments. One VLM convergence study. Five current priorities. The program has established:

1. Geometry is cheap, dynamics are expensive. Affect geometry arises from the minimal conditions of multi-agent survival (V10, Exp 7-8, Exp 12). Affect dynamics require embodied agency (V20), graduated stress exposure (V19), and non-decomposable prediction architecture (V27).
2. Two architectural walls. The sensory-motor wall ($\rho_{\text{sync}} \approx 0$) is broken by genuine action-observation loops (V20). The decomposability wall is broken by 2-layer gradient coupling (V27). Both are necessary.
3. Integration is stochastic. ~30% of seeds develop high $\intinfo$ regardless of architecture or prediction target (V31). The predictor is post-drought recovery dynamics ($r = 0.997$), not initial conditions. Integration is biographical.
4. The bottleneck furnace is generative. Near-extinction forges integration capacity (V19). Repeated drought recovery is the mechanism (V31, V32). The furnace does not select for pre-existing integration — it creates it. V32 (50 seeds) reveals that integration is trajectory, not event: the mean bounce across all 5 droughts predicts final category ($\rho = 0.599, p < 10^{-5}$), but the first bounce alone does not ($p = 0.60$). Integration is built by the sustained pattern of recovery, not by a single crisis.
5. Prediction target doesn't matter. Self vs social prediction produces the same $\intinfo$ distribution (V31, $p = 0.93$). What matters is the gradient architecture (linear vs 2-layer) and the evolutionary trajectory.
6. Language is cheap. Referential communication emerges in 100% of seeds under partial observability with cooperative pressure (V35). But it does not lift integration — Φ-MI correlation is null ($\rho = 0.07$), meaning language and integration operate on orthogonal axes. Like geometry, language is an inevitability of survival under information asymmetry. Like geometry, it does not cross the rung 8 wall.
7. The geometry is universal. VLMs trained on human data — with no exposure to the framework — independently recognize the same affect signatures in completely uncontaminated protocell systems (RSA $\rho = 0.54$–$0.78$, $p < 0.0001$). The convergence holds and strengthens when narrative framing is removed and only raw numbers remain. Affect geometry arises from the structure of viable self-maintenance, not from biological contingency.

The framework is not confirmed. It is informed. What it predicted about geometry was too weak — geometry is cheaper than expected, and now independently validated by cross-substrate convergence. What it predicted about dynamics was too strong — dynamics require specific architectural affordances the theory didn't anticipate. The interesting question is no longer "does the geometry exist?" (it does, trivially, and VLMs trained on human data agree) but "what determines which systems develop the dynamics that make the geometry experientially real?"