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The Oracle: A Compiler Learning Model that Holds Knowledge as a Ledger, Competence as Readable Rules, and Growth as Admitted State Transitions

Ben Horn · Version 2, 3 September 2026 · Machine Cognition · 11 pages · AI assistance disclosed in the manuscript

A cognitive system whose serving runtime contains no trained weights: knowledge as a ledger of individually cited sentences, competence as a chain of readable rules admitted through a held-out gate under a non-regression policy, self-modification as an unattended loop that authors and admits its own successor rules, and expression as typed routes whose outputs carry a derivation witness. Reported as counted on 2 and 3 September 2026, with every operational figure tied to a runtime identity, three same-day experiments with confidence bounds, universal claims narrowed to the evidence, and limits stated without softening.

The evidence bundle holds the measurement timestamps, the sha256 of each knowledge store, the gate ledger reconciliation, the admitted-directory census, the manifest tip and hash, the harness identities, every film specification with its seed, and the kernel schema, kernels, and measurement report. The held-out turn corpus is withheld to preserve the gate; its hash is published. A versioned source archive with an environment lockfile is not yet published and is stated as such in Appendix A. Version 1 is kept for the record; version 2 corrects its counts, resolves runtime identities, narrows its claims, and adds figures.

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