I’ve published AAEF v0.6.0.
AAEF — Agentic Authority & Evidence Framework — is an action assurance control profile for agentic AI systems.
The central idea is:
Model output is not authority.
When AI systems only generate text, many safety discussions focus on model behavior: accuracy, alignment, explainability, or refusal behavior.
But when AI agents can call tools, access data, delegate work, or perform actions in production systems, another question becomes critical:
Was this action authorized, bounded, attributable, and evidenced?
AAEF focuses on that action layer.
v0.6.0 is a planning and adoption-readiness release. It does not change the current active control and assessment baseline.
This release organizes planning artifacts for:
- implementers
- operators
- legal and compliance teams
- security architects
- risk owners and executives
It also adds planning material for authorization decision artifacts, implementer quick start guidance, operational responsibility, high-impact production architecture, legal/compliance applicability, and risk owner decision support.
AAEF is not a certification scheme, legal compliance claim, audit opinion, conformity assessment, or equivalence claim with external frameworks.
It is intended as a public-reviewable control profile for delegated authority, policy-enforced action boundaries, and verifiable evidence in agentic AI systems.
Release:
https://github.com/mkz0010/agentic-authority-evidence-framework/releases/tag/v0.6.0
Repository:
https://github.com/mkz0010/agentic-authority-evidence-framework
Feedback and critical review are welcome.
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