Reference
Glossary
The vocabulary of the Large People Model, defined precisely. Where a term is fixed on the Specification, its definition here is identical.
Every definition traces back to the Framework Specification, the single canonical source.
21 terms
A
- Autonomy spectrum
- The canonical five-point scale of decision autonomy: Human Only, Human Approved, Agent Assisted, Agent Supervised, and Agent Autonomous. Autonomy is earned by clearing a measurable confidence threshold set by the business owner, not engineering. Every new decision type starts at Agent Assisted.
In plain language
The five levels describing how much authority an agent has.
Used in
AI deployment decisions, confidence gates, and the Specification.
- SpecificationAI Amplification
C
- Compliance theater
- Controls that create the appearance of governance without reducing real operational risk. Real governance reduces entropy; compliance theater only signals control.
In plain language
Controls that look reassuring but do not reduce operating risk.
Used in
Governance diagnosis, the Laws, and workflow-control design.
- Governance ArchitectureThe Nine Laws
- Confidence gate
- Measurable thresholds a decision type must clear, set by the business owner, before it earns more autonomy.
In plain language
A measurable checkpoint an AI system must pass before gaining authority.
Used in
Governance controls, AI operating corridors, and autonomy reviews.
- SpecificationDiagnostic
- Control Readiness Index
- A composite score of how ready the operating model is to govern and safely automate work across the seven layers.
In plain language
A combined measure of readiness to govern and automate work.
Used in
The readiness diagnostic, maturity planning, and metrics.
- DiagnosticMetrics Library
D
- Decision latency
- The time between when a decision is needed and when an accountable decision is made, communicated, and acted on. LPM treats it as an operating-model signal, not just a team productivity issue.
In plain language
How long it takes an organization to make and act on a needed decision.
Used in
Decision diagnostics, operating metrics, and transformation work.
- The hidden cost of decision latencyMetrics Library
- Decision lineage
- The traceable record of who decided what, on what evidence, and what changed as a result.
In plain language
The traceable story of a decision from evidence through outcome.
Used in
Decision Architecture, governance, audit, and organizational learning.
- Decision ArchitectureSpecification
- Decision rights
- The explicit assignment of who makes, approves, is consulted on, and is informed of each decision type.
In plain language
The explicit rules for who decides, advises, approves, and is informed.
Used in
Decision Architecture, ownership design, and escalation planning.
- Decision Rights MatrixDecision Architecture
E
- Escalation path
- The predefined route by which a decision or exception moves to a higher authority when it exceeds an owner's threshold.
In plain language
The predefined route for an exception that exceeds someone's authority.
Used in
Decisions, governance controls, AI exceptions, and operating reviews.
- Governance ArchitectureDecision Architecture
G
- Governed agent
- Agents operated inside named human ownership, decision rights, boundaries, and audit, never as unaccountable actors.
In plain language
An AI agent operating inside named human ownership and explicit boundaries.
Used in
AI Amplification, Governance Architecture, and agent accountability tools.
- AI AmplificationGoverned Agent Accountability Checklist
H
- HITL (Human in the Loop)
- A human reviews and approves each action before it takes effect. The default for any new or high-stakes decision type.
In plain language
A human approves every action before it takes effect.
Used in
AI ownership modes, high-stakes workflows, and initial deployment.
- SpecificationAI Amplification
- HOTL (Human on the Loop)
- The agent acts, and a human monitors and can intervene or halt at any point.
In plain language
AI acts while a human monitors and can intervene.
Used in
Earned autonomy, monitored workflows, and exception management.
- SpecificationAI Amplification
- Human Operating Architecture
- The category of model the Large People Model belongs to: a structured architecture of how ownership, decisions, communication, information, platforms, governance, and AI operate as one system.
In plain language
The designed system behind how people, decisions, tools, and AI work together.
Used in
Category definition and the Framework Specification.
- SpecificationFramework
- Hybrid Workforce Architecture and Control
- The market category the Large People Model defines: the architecture and control layer for a workforce of humans and governed agents operating as one system.
In plain language
How an enterprise structures and controls work shared by people and AI.
Used in
Market positioning, AI readiness, and the Lapemo product bridge.
- SpecificationLapemo
K
- Knowledge Object
- Reusable, versioned operating-model assets authored once and rendered across education, knowledge objects, assessments, and the platform.
In plain language
A reusable, versioned operating-model tool or artifact.
Used in
Implementation work, the library, diagnostics, and Lapemo.
- Knowledge Objects
L
- Large People Model
- The Large People Model is a Human Operating Architecture: a structured model of how ownership, decisions, communication, information, platforms, governance, and AI operate as one system.
In plain language
The complete framework for seeing and improving how work operates.
Used in
Framework orientation, diagnostics, maturity, and implementation.
- SpecificationFramework
M
- Maturity phase
- One of the five named stages of the LPM Maturity Path, from Decision Clarity to Human-Machine Orchestration. The weakest foundation caps what is safe to automate now.
In plain language
One stage in the sequence for building safe operating-model readiness.
Used in
Maturity assessment, roadmaps, and implementation planning.
- Maturity PathSpecification
O
- Operating corridor
- The governed boundary within which an agent or decision type is permitted to act. Autonomy expands by widening the corridor, never by removing the boundary.
In plain language
The explicit boundary inside which an AI system may act.
Used in
AI Amplification, risk tiering, confidence gates, and human override.
- AI AmplificationSpecification
- Ownership map
- A Knowledge Object that assigns a single named human owner to each outcome, decision, and risk in the operating model.
In plain language
A record showing the one human accountable for each important outcome.
Used in
Identity & Incentives, implementation workshops, and Knowledge Objects.
- Ownership MapIdentity & Incentives
S
- Source of truth
- The single owned system or record that other systems and people defer to for a given piece of information.
In plain language
The one authoritative place for a specific kind of information.
Used in
Information Ecology, platform design, and AI grounding.
- Information EcologySource-of-Truth Map
- Supervised automation
- The agent runs a defined process end to end while a named human owns the exceptions, the audit, and the outcome.
In plain language
AI runs a defined process while a human owns exceptions and outcomes.
Used in
Workflow automation, operating corridors, and AI scaling decisions.
- SpecificationAI Amplification
- Supervisory Control Capacity
- The finite amount of agent oversight a single named human supervisor can carry before control degrades.
In plain language
The amount of AI oversight one human can perform reliably.
Used in
Agent scaling, ownership design, metrics, and the Ninth Law.
- SpecificationAI Amplification