RFC-0001: AEGIS Governance Architecture

RFC: RFC-0001
Status: Final (v1.0)
Frozen: 2026-03-26
Version: 0.2
Created: 2026-03-05
Updated: 2026-03-06
Author: AEGIS Initiative, AEGIS Operations LLC
Repository: aegis-governance
Target milestone: v1.0
Supersedes: None
Superseded by: None

Summary

This RFC defines the reference architecture for AEGIS™ (Architectural Enforcement and Governance of Intelligent Systems). AEGIS introduces a deterministic governance control plane between AI-generated intent and infrastructure execution, ensuring no action executes without explicit evaluation against capability, policy, authority, and risk constraints.

Motivation

Model alignment and content moderation influence outputs but do not guarantee control over operational side effects. When AI systems can take real actions — executing shell commands, modifying infrastructure, sending messages, querying data — policy documents and alignment techniques are insufficient. They describe what should happen. They do not prevent what should not.

AEGIS addresses this gap by enforcing complete mediation at the execution boundary:¹ every action is evaluated before it reaches external systems, and every decision is recorded immutably.

Guide-Level Explanation

Think of AEGIS as a security guard stationed between an AI agent and everything the agent can touch. When an AI wants to take an action, it submits a proposal. The security guard checks three things: is this agent allowed to do this, does it need human approval, and could this cause irreversible harm? If any check fails, the action never executes.

The guard also keeps a notebook. Every proposal, every decision, every reason — written down in a form that cannot be altered after the fact. If something goes wrong, the notebook is the authoritative record.

Reference-Level Explanation

1. Architectural Principles

1. Deterministic Governance: same inputs and policy version produce same outcome.
2. Capability-First Authorization: every action maps to a predefined capability.
3. Explicit Authority Attribution: every request is bound to an authenticated actor.
4. Default Deny: absence of explicit authorization yields denial.²
5. Complete Auditability: every decision is recorded and replay-verifiable.¹
6. Fail-Closed Safety: subsystem uncertainty cannot result in implicit allow.²

2. System Context

flowchart TD
    A[AI Agent or Copilot] --> B[Governance Gateway]
    B --> C[Decision Engine]
    C --> C1[Capability Registry]
    C --> C2[Policy Engine]
    C --> C3[Risk Engine]
    C --> D[Audit System]
    C --> E[Tool Proxy Layer]
    E --> F[External Systems]

3. Component Responsibilities

Governance Gateway: validate request schema and semantic constraints; validate actor identity binding; reject malformed requests; route valid requests to Decision Engine.

Decision Engine: perform capability check; evaluate policy precedence; evaluate contextual risk thresholds; produce one deterministic outcome (ALLOW, DENY, ESCALATE, REQUIRE_CONFIRMATION).

Capability Registry: maintain canonical capability definitions and actor-capability grants; support revocation and expiration semantics.

Policy Engine: evaluate policy conditions against request context; apply deterministic precedence rules; emit policy trace for auditability.

Tool Proxy Layer: execute only authorized decisions; enforce runtime constraints; prevent direct infrastructure bypass; record execution telemetry.

Audit System: append immutable decision records; support retrieval by request/actor/session; provide evidence for replay and compliance.

4. Request Lifecycle Sequence

sequenceDiagram
    participant AG as AI Agent
    participant GW as Governance Gateway
    participant DE as Decision Engine
    participant CR as Capability Registry
    participant PE as Policy Engine
    participant RE as Risk Engine
    participant AS as Audit System
    participant TP as Tool Proxy
    participant EX as External System

    AG->>GW: Submit action request
    GW->>GW: Validate schema and metadata
    GW->>DE: Forward validated request
    DE->>CR: Check capability grant
    CR-->>DE: grant/deny
    DE->>PE: Evaluate policies
    PE-->>DE: policy outcome + trace
    DE->>RE: Evaluate contextual risk
    RE-->>DE: risk score
    DE->>AS: Persist decision record
    AS-->>DE: audit_id
    alt Decision is ALLOW or REQUIRE_CONFIRMATION approved
      DE->>TP: Execute with constraints
      TP->>EX: Controlled action
      EX-->>TP: Result
      TP-->>AG: Result + audit_id
    else Decision is DENY or ESCALATE
      DE-->>AG: Denied/Escalated + reason + audit_id
    end

5. Security Properties and Guarantees

6. Failure Mode Analysis

Drawbacks

• Adds latency to every AI action. The governance evaluation path introduces overhead. RFC-0002 specifies SLO targets to bound this.
• Requires capability definitions to exist before agents can operate. Cold-start and onboarding complexity is non-trivial.
• Default-deny posture will produce friction during initial deployment until registries are tuned to the operational environment.
• Audit log growth is unbounded over time and requires operational management.

Alternatives Considered

Model-level alignment only: Relies on the model to self-enforce constraints. Insufficient because model behavior is non-deterministic and cannot provide audit evidence of what was allowed or denied.

Network-level controls only: Firewalls and API gateways can restrict what systems an agent can reach but cannot evaluate the semantic intent of a request before it is made.

Human-in-the-loop for all actions: Provides strong safety guarantees but eliminates the operational value of AI agents at scale. AEGIS reserves human escalation for genuinely ambiguous or high-risk decisions.

Policy-as-code without runtime enforcement: Tools like OPA³ can evaluate policy but require integration with an execution boundary. AEGIS provides that boundary as a first-class architectural component.

Compatibility

This is the foundational architecture RFC. All other RFCs are downstream of it. No prior AEGIS deployments exist at the time of this draft.

Implementation Notes

RFC-0002 specifies the runtime API. RFC-0003 specifies the capability registry and policy language. Implementers should read in order: RFC-0001, RFC-0002, RFC-0003, RFC-0004.

Open Questions

• Should the Risk Engine be a separate RFC or remain within RFC-0001?
• Should AEGIS define a formal conformance test suite for architecture compliance?

Success Criteria

• A compliant runtime can be built from this RFC and RFC-0002 alone
• Every action that reaches an external system can be traced to an audit record
• No action executes when the governance path is unavailable

References

AEGIS™ | “Capability without constraint is not intelligence”™
AEGIS Initiative — AEGIS Operations LLC