Beyond Persistence: Causal Cross-Process Cognitive Influence in a Governed Agent Architecture
Gabriel Allit · Zenodo (CERN European Organization for Nuclear Research) · 2026
Persistent state is often credited as memory or learning even when it never affects a later decision. This preprint introduces Persistent Cognitive Influence (PCI), an operational evaluation discipline that separates recording, durable persistence, fresh-process retrieval or reload, canonical cognitive consumption, attributable downstream influence, independent outcome verification, and comparative improvement. Applied to four EvoMind mechanisms at a pinned August 2026 evidence cut, the study reports: (1) grounded user-fact recall across a fresh process with role attribution, session/project isolation, and absent-fact abstention; (2) relational entity grounding that survives restart and resolves indirect run/node references to verified artifacts, including stale-mutation detection; (3) a cognitive performance self-model whose verified-outcome-derived aggregate bias moved from 0.30 to 0.405 and automatically reloaded as 0.405 in a fresh process; and (4) structural recovery reuse where a persisted ACTIVE principle caused treatment to make zero recovery resynthesis calls versus one in an isolated control, with both paths passing the same downstream verification/release gate. The evidence is first-party internal software validation. The paper does not claim unrestricted transfer, general semantic recall, aggregate task-performance improvement, external replication, or artificial general intelligence. The deposit includes the publication PDF and source, a supplementary evidence PDF and source, claim/evidence and reproducibility records, machine-readable results, provenance, licensing, and cryptographic hashes. Evidence cutoff: EvoMind repository state c2e4a219a7c1ff11a61e2639c112daa9008f17b6, 2026-08-27T11:23:55Z. Rights: Copyright © 2026 Gabriel Allit. All rights reserved. See LICENSE.txt included with this research object.