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Bridging the strategic and the speculative
A short “map” post that compresses three longer essays into a single causal sequence. It explains why AI inevitably moves from centralized general intelligence to hierarchical specialization—not as a design choice, but as a consequence of economics, verification costs, and liability once intelligence becomes cheap.
The dividing line between generalist and specialist AI isn’t capability, but the cost of verification. Where correctness is cheap to check, generalists win; where it’s expensive and liability-laden, a stack of risk-bearing institutions emerges to manage the price of being wrong.
When fluent writing becomes cheap, elegance stops being a signal of thought. This essay argues that judgment, constraint, and the ability to stop are the new proofs of human cognition in an age of infinite language.
When content becomes free, studios don’t sell files—they sell validity. This piece outlines how canon functions as a runtime, enabling creators to escape entropy and build meaning that actually accumulates.
Generative AI collapses the cost of creation, but it doesn’t eliminate value—it displaces it. When anyone can produce infinite variations in any style, identity stops being implicit and becomes contested. This piece examines the economic inversion that follows, and why coherence—not creation—becomes the scarce resource.
When creation becomes frictionless, origin stops being obvious. This piece traces why enforcement can’t scale to generative imitation—and what quietly fails when identity no longer resolves automatically.
The next phase of AI won’t be designed—it will evolve. As frontier scaling hits economic and operational limits, specialization becomes the only viable path forward. The platforms that adapt fastest will define the new equilibrium.
While everyone debates AGI timelines, economic and regulatory constraints are already forcing AI toward hierarchical specialization.
