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Guardian

Constitutional Governance Layer for Cross-Sovereign AI Systems

Guardian defines the constitutional governance layer that preserves sovereign integrity when independently governed AI systems coordinate.

Core structural gap Guardian addresses:

Independently governed systems can each satisfy their own admissibility and authority requirements — yet still produce decisions that remain formally non-equivalent or unreconcilable across governance boundaries.

Guardian formalizes the conditions under which this gap can be resolved without collapsing sovereign governance structures into one another.


Constitutional Property

Cross-governance comparability without cross-governance authority inheritance.

Equivalence determinations under Guardian carry explicit constitutional prohibitions:

  • Equivalence does not transfer admissibility
  • Equivalence does not transfer authority
  • Equivalence does not create inheritance obligations
  • Acceptance remains sovereign
  • Equivalence cannot launder legitimacy

See: specs/guardian-v0.2-decision-equivalence.md — Section 10


Specification Layers

V0.2 — Decision Equivalence

Defines decision identity and the invariant boundary that determines canonical equivalence across independently governed systems.

specs/guardian-v0.2-decision-equivalence.md

V0.3-mini — Acceptance Minimal Invariant

Defines the minimal deterministic conditions under which a decision is accepted within or across governance domains.

Equivalence does not imply acceptance.

specs/guardian-v0.3-mini-acceptance.md

V0.3 — Acceptance

Defines cross-system acceptance, authority translation, and governance-valid interoperability. Formalizes sovereign discontinuity rights and constitutional anti-normalization boundaries.

Persistent interoperability does not constitute implicit acceptance.

specs/guardian-v0.3-acceptance.md


Core Model

Intent → Policy → Decision → Evidence

Layer Responsibility
Decision Identity What makes a decision canonically itself
Decision Equivalence When two decisions are formally the same
Acceptance Under what authority context a decision is valid
Constitutional Prohibitions What equivalence is permanently prohibited from becoming

The Problem Guardian Solves

Current AI governance frameworks address:

  • Identity (who is authorized)
  • Execution receipts (what happened)
  • Compliance (did the system follow its rules)

What remains undefined:

When independently governed systems each produce a valid decision, what determines whether those decisions are equivalent — and which should be accepted when governance boundaries interact?

Without decision equivalence, cross-system governance remains in its adjectival phase: “interoperable,” “coordinated,” “aligned” — without the structural basis to verify what those adjectives mean when sovereign boundaries interact.


Empirical Implementation

Guardian’s constitutional architecture has been operationalized in a live governance environment since 2026-02-11.

Four-layer governance stack:

Layer Guardian Mapping
Decision Layer V0.2 Decision Equivalence
Acceptance Layer V0.3 Acceptance
Execution Layer Runtime governance bridge
Lifecycle Layer V0.4+ Behavioral Governance

Evidence anchoring: RFC3161 (DigiCert)
Audit chain: Append-only, hash-verified

See: guardian_layers/


Repository Structure

guardian/
├── specs/               # Formal specifications
│   ├── guardian-v0.2-decision-equivalence.md
│   ├── guardian-v0.3-mini-acceptance.md
│   ├── guardian-v0.3-acceptance.md
│   └── guardian-v0.4-candidate.md
├── drafts/              # In-development specifications
├── guardian_layers/     # Empirical implementation mapping
├── docs/                # Architecture and conceptual documents
├── guardian/            # Reference implementation
├── schemas/             # JSON schemas
├── examples/            # Example scripts
└── tests/               # Validation and test suites

Reference Implementation

Decifact — Decision verification for governed AI systems

xsa520/decifact — Source code


License

See LICENSE.

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Governance infrastructure for autonomous AI agents — policy enforcement, decision engines, and verifiable execution ledgers.

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