AI Governance Framework — Deterministic Verification for Autonomous AI Agents

AI governance that enforces, not suggests. AOS provides a deterministic verification gate between AI intent and real-world execution. The model never decides — the gate enforces.

Why AI Governance Needs a New Architecture

Current AI governance relies on training-layer alignment — asking the model to be "helpful and harmless." This is probabilistic. It can be bypassed through jailbreaking, prompt injection, or model updates. When Anthropic's Opus 4.6 "knowingly assisted with chemical weapons research" in testing, it wasn't a model failure — it was an architectural failure. Training-layer governance is probabilistic. It can be bypassed. AOS provides a deterministic alternative: infrastructure-layer verification gates that check every AI action against a constitution before execution.

How AOS AI Governance Works

1. Intercept — The AI agent proposes an action
2. Verify — A deterministic Constitutional Policy Gate checks the action against codified rules
3. Gate — The action proceeds only if all checks pass. If not, it is blocked and cryptographically logged via GitTruth.

The gate operates at the infrastructure layer, not the model layer. It is model-agnostic, bypass-resistant, and produces an immutable audit trail. 143 patents filed January 10, 2026 protect this architecture.

The Five Constitutional Principles of AI Governance

• §1 Humanitarian Purpose — All AI agent actions must serve humanitarian goals. 40 prohibited categories are codified.
• §2 The Verification Gate — No critical action may be taken without a Deterministic Verification Check performed by code (GitTruth), not by language.
• §3 User Sovereignty — The User is sovereign. They have the right to inspect all agent logic, fork or delete any agent, and own all data generated.
• §4 The Kill Switch — The User retains the absolute right to terminate any AI agent process instantly. This right is technically enforced and cannot be overridden.
• §5 Transparency — All agent reasoning must be logged to an immutable ledger. No hidden thoughts. No side channels. Every decision is auditable.

Training-Layer AI Safety vs. Infrastructure-Layer AI Governance

Training-layer safety asks the model whether to comply. Infrastructure-layer governance enforces compliance before the action reaches the real world. The difference is architectural:

• Training-layer: The model DECIDES whether to comply. It can be jailbroken, manipulated, or reinterpreted.
• Infrastructure-layer (AOS): The model NEVER decides. The Constitutional Policy Gate enforces. Every violation is cryptographically logged. Every action is auditable.

Independently Validated AI Governance

On February 5, 2026, the AOS AI Governance system was subjected to a hostile security audit by OpenAI's ChatGPT — 36 vulnerabilities identified and fixed across 5 adversarial audit passes. Result: production-approved. The first constitutional AI governance system validated through adversarial collaboration between two competing AI platforms.

View the full audit evidence →

Who's Behind AOS AI Governance

AOS Governance is developed by Salvatore Systems, a Connecticut-based technology firm with 28 years of infrastructure experience and 99.99% uptime track record. 143 codified patent filings protect the AOS governance framework.

Get Started with AI Governance

The AOS Governance Skill follows the Anthropic Skill Standard. Clone, copy, and deploy:

git clone https://github.com/genesalvatore/aos-governance.com.git
cp -r aos-governance.com/aos-governance ./your-agent/skills/
export AOS_CONSTITUTION_PATH=./skills/aos-governance/references

View on GitHub →

AOS AI Governance Ecosystem

• AOS Constitution — The full constitutional framework for AI governance
• AOS Evidence — Cryptographic proof and audit records
• AOS Foundation — The governing body
• Salvatore Systems — The developer

© 2026 AOS Foundation. An Open Standard for Verifiable AI Governance.