AEL v0.1 — Advisory Execution Layer

AEL v0 — Advisory Execution Layer (Reference Specification) AEL v0 is a minimal, deterministic reference specification for an Advisory Execution Layer designed to govern AI-initiated actions under uncertainty. Rather than improving prediction accuracy or alignment quality, AEL focuses on a different failure mode of intelligent systems: acting when non-action, delay, or human intervention would be safer. The Advisory Execution Layer operates as an external, model-agnostic control module positioned between an AI system’s proposed action and its execution.It evaluates actions across a small set of explicitly defined epistemic and structural risk dimensions, such as: uncertainty density in the input state irreversibility of the proposed action correlation pressure between information sources narrative acceleration and decision instability Based on deterministic scoring and transparent thresholds, AEL v0 produces one of three advisory outcomes: ALLOW — execution is structurally acceptable DELAY — execution should be postponed pending additional information HALT — execution should not proceed Crucially, delay and refusal are treated as first-class successful outcomes, not as failures of intelligence. This version (v0) provides: a conceptual architecture of the Advisory Execution Layer formal definitions of core risk metrics a deterministic decision logic model an auditable explanation interface via reason codes illustrative cross-domain scenarios (e.g. automated finance, infrastructure control, agent orchestration) AEL v0 is intentionally lightweight, interpretable, and hardware-agnostic.It is designed as a foundational specification, suitable for further formalization, implementation, and integration into safety-critical or regulated AI systems. All materials are released openly to enable critique, reuse, and extension by the research and open-source community.