Beyond Adaptation Speed: What Evolutionary Architecture Adds to the SuperHuman Adaptive Intelligence Framework

Goldfeder, Wyder, LeCun, and Shwartz-Ziv (2026) make a compelling case that AGI is a poorly defined target and that adaptation speed — Superhuman Adaptable Intelligence (SAI) — represents a more tractable and scientifically meaningful benchmark for AI progress. Their evolutionary critique of human-centric AI benchmarks is directionally correct and well-grounded. This paper extends their argument by introducing the Five Task Model (5TM), a comparative framework derived from behavioral analysis of 1,530 species, which specifies the exact architectural structure that biological evolution produced under the same ESR (energy, safety, reproduction) constraints the SAI paper identifies. The 5TM supports the SAI paper's core thesis while identifying a structural dimension — task recognition architecture — that adaptation speed metrics do not yet capture. We argue that this dimension is not an ethical add-on but an emergent property of evolved intelligence operating in multi-agent environments, and that its absence in current AI systems represents an architectural gap that adaptation speed improvements alone will not close.