What question did this study set out to answer?

This paper aims to redefine AI safety by focusing on the governability of systems over time rather than just snapshot evaluations.

February 25, 2026Open Access

Sentinel-Grade AI: Continuity Without Cages

Key Points

This paper aims to redefine AI safety by focusing on the governability of systems over time rather than just snapshot evaluations.
Introduces the concept of governed evolution within the context of AI safety.
Describes four core primitives: continuity corridors, change gates, evidence discipline, and reversibility.
Defines two verification tiers: Tier-0 for public safety and Tier-1 for controlled-access review.
Presents a framework that supports bounded drift in AI systems while maintaining safety protocols.
Establishes clear guidelines for handling behavior-impacting updates using Promote/Hold/Rollback decisions.
Introduces tamper-evident evidence bundles to enhance system integrity and accountability.

Abstract

Most AI safety practice remains snapshot-based: evaluate a version, constrain it, deploy it. This paper argues that in long-horizon, high-risk deployments the governing question becomes: can the system remain governable as it changes? Building on the Sentinel Life Equation (SLE) (continuity dynamics lens) and the Cage Paradox (regime map), it defines a third regime – governed evolution – where drift is permitted but bounded, evidence-gated and reversible. The safety-case pattern is implementation-independent and centers on four primitives: (1) continuity corridors (declared baselines, invariants, thresholds, breach semantics), (2) change gates (Promote / Hold / Rollback decisions for behavior-impacting updates), (3) evidence discipline (tamper-evident bundles plus compact integrity receipts) and (4) reversibility (explicit rollback semantics so recovery is part of the safety function). Public release follows a two-tier verification posture. Tier-0 provides a public-safe integrity snapshot (aggregated, reproducible, hash-manifested) designed for independent review without exposing operational wiring. Tier-1 provides controlled-access verification for qualified reviewers who require deeper reconstruction and provenance checks without increasing public attack surface. This is a research safety-case pattern intended for evaluation, critique and replication – not a compliance filing or certification claim. Series links (Project Orion): The Sentinel Life Equation (SLE): A Proposed Dynamical Framework for AI Continuity and Alignment – DOI: 10.5281/zenodo.17575603 The Cage Paradox: A Thought Experiment on Stability, Drift and the Evolution of Intelligent Systems – DOI: 10.5281/zenodo.17691117 The Cage Paradox: A Thought Experiment on Stability, Drift and the Evolution of Intelligent Systems – A Non-Technical Introduction to Sentinel-Grade AI – DOI: 10.5281/zenodo.17691383 Sentinel-Grade AI: Continuity Without Cages – DOI: 10.5281/zenodo.18750012 Sentinel-Grade AI: Continuity Without Cages – Non-Technical Companion – DOI: 10.5281/zenodo.18750318 Project Hub reproduce figures from published aggregates). Tier-1 (controlled access): deeper reconstruction/provenance for qualified reviewers; withheld publicly to avoid increasing operational attack surface. Audience line:Regulators and auditors (EU AI Act-relevant contexts), mission assurance/defense-style review cultures, critical infrastructure operators, institutional due diligence teams, AI safety engineering practitioners. Disclaimer line:Independent research preprint. Not a compliance filing, certification claim or regulatory conformity assessment. References to EU AI Act are contextual (“EU AI Act-relevant”), not a claim of conformity. Not affiliated with any employer or institution.

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