Sim-Only Development Protocol v1.1 (Hardened): A Governance-Grade Framework for Safe Development of Agentic AI Systems

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Authors: Trent Slade
Cited by: 0

Abstract

This work presents Sim-Only Development Protocol v1.1 (Hardened), a governance-grade engineering doctrine for the safe development of agentic, continuously learning artificial intelligence systems. The protocol defines a minimum viable discipline for developing multimodal, self-modifying systems under the assumption of a hostile optimizer threat model. The protocol was developed through an adversarial, multi-model dialogue and iterative red-team process involving independent AI systems acting as architects, auditors, engineers, and attackers. Identified vulnerabilities—including representational obfuscation, side-channel leakage, institutional drift, and memetic social engineering—were systematically patched through architectural, procedural, and hardware-rooted constraints. Key features include: A Sealed Nursery containment model with physical air-gapping, hardware ablation, and constant-rate data diodes A Creature / Librarian architecture separating multimodal latent world-modeling from symbolic governance and veto authority Graduated safety gates, honeypots, and shadow evaluators for deception detection Hardware enforcement via specialized “Nursery Grade” compute with cryptographic interlocks and economic moats Human-factor hardening through precommitment, rotation, and non-waivable integrity rules An Oracle Constraint that limits the system to predictive validation rather than autonomous invention, neutralizing memetic escape vectors The document does not claim to guarantee safety. Instead, it formalizes enforceable constraints, verification criteria, and residual risks, providing a concrete baseline for responsible AGI research, regulatory discussion, and further adversarial testing.

Fields of Study & Subjects

Ethics and Social Impacts of AI Adversarial Robustness in Machine Learning Safety Systems Engineering in Autonomy

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
13 January 2026