Detailed answer
Key answer: The exact deliverables depend on the scope, maturity, consequence level, and selected service.
Core explanation
The exact deliverables depend on the scope, maturity, consequence level, and selected service.
A focused engagement should produce clear, usable artifacts rather than only abstract discussion.
Possible deliverables include:
AI Action Inventory
A structured list of actions the AI system may recommend, prepare, initiate, authorize, or execute.
This helps distinguish harmless outputs from actions that create meaningful consequence.
Execution Boundary Map
A visual or written representation of where AI output changes status:
information → recommendation → proposed action → authorization → execution → consequence
L0–L3 Context Classification
An initial classification of actions according to consequence, reversibility, governance need, and responsibility.
This helps determine where lighter or stronger governance is appropriate.
Authority and Responsibility Matrix
A map of:
- who may propose;
- who may judge;
- who may authorize;
- who may change rules;
- who may stop execution;
- who remains responsible.
Reliability-Rule Categories
An outline of the legal, safety, operational, institutional, contractual, or domain-specific rules that should influence execution.
Allow / Block / Escalate Table
A concept-level framework showing which actions may proceed, which must stop, and which require stronger review.
Governance Gap Analysis
A description of missing or weak conditions, such as:
- undefined authority;
- unclear responsibility;
- symbolic human approval;
- absent execution boundaries;
- ungoverned rule changes;
- direct Agent-to-execution pathways;
- lack of escalation.
Judgment–Governance Architecture
For deeper engagements, a high-level design showing how Judgment Root Node, LERA-J, LERA-G, WRS, RCC, ECS, and the Execution Boundary may relate to the selected use case.
Pilot Plan
A bounded test design with scenarios, roles, governance states, expected outcomes, and evaluation indicators.
Executive Report and Roadmap
A summary of the main risks, priorities, recommended phases, and decisions required from leadership.
The deliverables do not represent a safety guarantee, legal approval, certification, or automatic claim of complete LERA implementation.
Their purpose is to make execution power visible and provide a structured pathway toward governed deployment.
A strong engagement should leave the customer able to answer:
- What can the AI execute?
- Where is the boundary?
- Who has authority?
- Who is responsible?
- Which rules apply?
- What must be blocked?
- What must be escalated?
- What should be built next?
The customer should receive not only an assessment of risk, but a clearer architecture of control.