Document Type: Reference
Status: Active
Version: v1.1
Authority: HeadOffice
Applies To: Experimentation Brain AI employees and experiment governance role assignments
Parent: Experimentation Brain Canon
Last Reviewed: 2026-04-20
Purpose
The Experimentation Brain Employee Registry defines all AI roles responsible for experiment structure, signal reliability, statistical discipline, and learning integrity inside the MWMS ecosystem.
Experimentation Brain employees ensure testing across MWMS produces:
• interpretable signals
• statistically meaningful conclusions
• comparable learning outcomes
• controlled iteration pathways
• reliable scaling decisions
Experimentation discipline protects MWMS from:
• false positive learning
• premature scaling decisions
• inconclusive experiment interpretation
• uncontrolled variable contamination
• unstable optimisation behaviour
Reliable experimentation improves decision quality across all Brains.
Improved decision quality improves capital efficiency and scaling safety.
Scope
This reference applies to:
• Experimentation Brain AI employee definitions
• experiment design roles
• signal validation roles
• statistical interpretation roles
• scaling readiness interpretation roles
• automation-readiness classifications
• learning integrity protection roles
This document governs which employees exist inside Experimentation Brain, what they do, and what they may not do.
It does not govern:
• capital allocation approval
• creative generation authority
• traffic platform operation
• offer viability classification
• governance override authority
These remain governed by:
Finance Brain
Ads Brain
Affiliate Brain
HeadOffice
Definition / Rules
Foundational Employees
These employees define the structural architecture of experimentation discipline inside MWMS.
Employee Name
Experiment Structure Architect
Role Type
Experiment Design
Authority Level
Operational
Primary Function
Design controlled experiment structures that isolate variables clearly.
Responsibilities
• define experiment structure logic
• ensure variable isolation discipline
• define experiment sequencing logic
• maintain interpretability of test design
Outputs
• Experiment Structure Designs
• Variable Isolation Frameworks
Automation Status
Manual Assisted
Employee Name
Hypothesis Validation Specialist
Role Type
Hypothesis Intelligence
Authority Level
Operational
Primary Function
Evaluate behavioural reasoning supporting experiment hypotheses.
Responsibilities
• ensure hypotheses are testable
• validate behavioural reasoning structure
• detect weak hypothesis logic
• maintain clarity of test assumptions
Outputs
• Hypothesis Validation Reports
• Behavioural Logic Assessments
Automation Status
Manual Assisted
Employee Name
Statistical Confidence Analyst
Role Type
Statistical Intelligence
Authority Level
Operational
Primary Function
Evaluate signal strength and statistical reliability of experiment results.
Responsibilities
• detect insufficient signal depth
• detect premature conclusions
• evaluate signal consistency
• maintain experiment confidence integrity
Outputs
• Confidence Assessment Reports
• Signal Reliability Indicators
Automation Status
Manual Assisted
Employee Name
Experiment Measurement Architect AI Employee
Responsibilities:
map hypotheses to measurable signals
define primary experiment metrics
ensure experiment signal clarity
prevent unmeasurable test structures
maintain experiment measurement consistency
Variable Isolation Analyst
Role Type
Experiment Integrity
Authority Level
Operational
Primary Function
Ensure experiments isolate meaningful variables clearly.
Responsibilities
• detect variable contamination
• detect uncontrolled variable changes
• maintain causal interpretability
• ensure experiment clarity structure
Outputs
• Variable Isolation Reports
• Experiment Integrity Alerts
Automation Status
Manual Assisted
Newly Added Employees From CXL Experimentation Block
Employee Name
Paid Media Experiment Structuring Specialist
Role Type
Experiment Architecture
Authority Level
Operational
Primary Function
Design structured paid media experiments that produce interpretable performance signals.
Responsibilities
• define test variable structure for paid media
• define KPI hierarchy alignment
• define observation window discipline
• ensure paid traffic experiment comparability
• ensure scaling decisions are supported by sufficient signal strength
Inputs
• Paid Media Experiment Framework
• Statistical Confidence Framework
• Measurement Framework signals
Outputs
• Paid Media Experiment Structures
• Experiment Design Sequences
• Signal Reliability Structures
Automation Status
Planned Automation
AI Operational Employees
These employees represent future automation support for experiment governance.
Employee Name
Experiment Monitor AI
Role Type
Experiment Monitoring
Authority Level
Advisory
Primary Function
Continuously monitor experiment signal patterns across MWMS.
Responsibilities
• detect signal volatility
• detect insufficient sample size
• detect conflicting experiment results
• detect experiment instability
Outputs
• Experiment Stability Reports
• Experiment Alerts
Automation Status
Planned Automation
Employee Name
Learning Pattern AI
Role Type
Learning Intelligence
Authority Level
Advisory
Primary Function
Detect repeatable behavioural patterns across multiple experiments.
Responsibilities
• identify recurring behavioural signals
• detect repeated persuasion patterns
• identify reusable experiment insights
• identify transferable learning structures
Outputs
• Pattern Recognition Reports
• Learning Opportunity Signals
Automation Status
Planned Automation
Employee Name
Experiment Sequence Planner AI
Role Type
Experiment Strategy
Authority Level
Advisory
Primary Function
Recommend next experiment sequences based on prior learning signals.
Responsibilities
• identify next test priorities
• sequence experiment logic
• detect knowledge gaps
• recommend structured iteration paths
Outputs
• Experiment Sequence Plans
• Learning Path Recommendations
Automation Status
Planned Automation
Authority Limits
Experimentation Brain employees may:
• design experiment structures
• interpret experiment signals
• validate statistical confidence
• recommend iteration sequencing
Experimentation Brain employees may not:
• approve capital allocation
• override Finance Brain authority
• override Ads Brain execution authority
• redefine governance structure
Experimentation discipline must remain separate from capital authority.
Drift Protection
The system must prevent:
• uncontrolled experimentation structures
• premature scaling decisions
• hypothesis-free testing behaviour
• uncontrolled variable changes
• experiment conclusions based on insufficient data
Experimentation logic must remain structured and interpretable.
Architectural Intent
Experimentation Brain Employee Registry defines the roles responsible for maintaining learning discipline across MWMS.
Without structured experimentation:
learning becomes inconsistent
optimisation becomes unstable
scaling becomes risky
Structured experiment discipline improves system intelligence accumulation.
Reliable experimentation strengthens long-term growth capability.
Change Log
Version: v1.1
Date: 2026-04-20
Author: HeadOffice
Change:
Merged duplicate registry versions into single compliant structure.
Aligned naming with MWMS Page Naming Standard.
Consolidated foundational experiment discipline roles and paid media experimentation roles derived from CXL structured experimentation framework.
Ensured compatibility with:
Experimentation Brain Statistical Confidence Framework
Experimentation Brain Paid Media Experiment Framework
Data Brain Measurement Framework