A formal framework for provably safe AI derived from first principles. One postulate – a finite structure exists – yields a mathematical proof that any system certifying solutions over finite structures must converge to a single architecture: fixed space, decidable test, append-only memory. Five theorems (soundness, safety, identifiability, universality, completeness), 25 properties, and three invariants (I1–I3) are derived from the postulate. The inner pipeline is total on valid finite encodings, deterministic under fixed features and protocol, with an append-only comparison cache. Formalized over finite binary trees with decidable equality. Implemented in Python (runtime solver, ARC-AGI tasks) and Swift (compile-time proof: the type checker verifies encoded constraints).
Daniil Strizhov (2026) studied this question.
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