Published Research
Foundational Research Series
Paper I
Deterministic Runtime Enforcement Architecture
Defines the fail-closed runtime boundary between AI-generated intent and operational execution.
Included in the v1.0.1 archive
Paper II
Execution Layer Governance
Frames runtime control as a governance primitive rather than a logging or observability layer.
Included in the v1.0.1 archive
Paper III
Governed Execution Artifact Standard v1.0
Introduces the canonical artifact structure used for policy evaluation, authority, and traceability.
Included in the v1.0.1 archive
Paper IV
Execution Doctrine
Establishes the operational doctrine behind authority-bound execution for enterprise AI systems.
Included in the v1.0.1 archive
Latest White Papers
Paper V
Training AI to Understand Emotions
A governed multimodal architecture for emotional signal capture and attested calibration in language model alignment.
Paper VI
SovereignGate: XRPL-Native Governance Enforcement
Deterministic governance enforcement architecture for autonomous financial actors operating on the XRP Ledger.
Paper VII
Agentic Governance Benchmark (AGB)
Measurement instrument for evaluating AI governance enforcement maturity across deterministic, cryptographic, and operational dimensions. ExecLayer self-scored 97.5 at Sovereign tier.
Paper VIII
Override Health Benchmark (OHB)
Auditor-facing measurement instrument for evaluating the structural integrity of AI override, escalation, and human-in-the-loop mechanisms.
Book
The End of Probabilistic Governance
ISBN 9798180419286
Published by ExecLayer Media.
Archive Metadata
Version: v1.0.1
Publisher: ExecLayer Inc., Wilmington, Delaware, United States
Release Date: March 2026
Version DOI: https://doi.org/10.5281/zenodo.18521539
Concept DOI: https://doi.org/10.5281/zenodo.18521538