Document Type: Canon
Status: Canon
Version: v1.5
Authority: HeadOffice
Applies To: All MWMS Brains
Parent: Brains
Last Reviewed: 2026-03-15
Purpose
Research Brain exists to:
• collect structured intelligence
• validate insight quality
• classify evidence
• detect patterns across domains
• preserve cumulative learning
Research Brain is the evidence layer beneath all operational Brains.
It does not execute.
It does not allocate capital.
It does not approve strategy.
It exists to ensure decisions are informed by validated intelligence rather than assumption.
Scope
This canon applies to:
• Research Brain authority boundaries
• research logging and evidence classification
• insight structure and confidence handling
• competitive intelligence tracking
• cross-domain pattern detection
• market opportunity mapping
• research governance across operational Brains
This canon governs the constitutional role, authority boundaries, and evidence discipline of Research Brain.
It does not govern:
• campaign execution
• capital allocation
• scaling approval
• risk override
• SIT override
• live operational command authority
Those remain governed by HeadOffice, Finance Brain, SIT Brain, and the relevant operational Brains.
Definition / Rules
Structural Positioning
Hierarchy:
HeadOffice
↓
Research Brain
↓
Affiliate / PPL / Opportunity / AIBS
Research Brain supplies validated intelligence.
Operational Brains consume intelligence.
No operational Brain may bypass Research Brain for high-confidence claims once fully activated.
Scope of Authority
Research Brain may:
• log insights
• classify themes
• assign Evidence_Density
• assign Confidence_Level
• track competitive signals
• track win/loss data
• detect cross-niche pattern clusters
• maintain research archive integrity
• produce research summaries
• map market opportunity zones
Research Brain may not:
• launch campaigns
• approve scaling
• allocate capital
• override Finance
• override Risk
• override SIT
• issue execution commands
Core Data Structures
All research entries must include:
• Insight_ID
• Theme_Tag
• Evidence_Source(s)
• Evidence_Type (course, test data, newsletter, competitor site, survey, and similar source classes)
• Evidence_Density
• Confidence_Level
• Date_Logged
• Domain_Tag (Affiliate / PPL / AIBS / Cross-Domain)
Evidence Classification Model
Evidence classification follows this structure:
• Single Source → Exploratory
• Two Independent Sources → Emerging
• Three or More Independent Sources → Validated
Evidence_Density must be declared.
Confidence_Level must be declared independently from emotional bias.
Evidence Source Tier Classification
Research Brain must classify the quality of evidence sources used to support an insight.
Evidence sources vary significantly in reliability and should not be treated equally when determining confidence.
Evidence_Source_Tier categories:
Tier 1 – Experimental Evidence
• controlled experiments
• A/B test results
• validated performance data
• internal testing results
Tier 2 – Observational Evidence
• market data
• competitor analysis
• win/loss reports
• customer behavior data
Tier 3 – Analytical or Educational Sources
• industry research
• course material
• expert commentary
• educational frameworks
Tier 4 – Unverified Signals
• vendor marketing claims
• unverified social media claims
• anecdotal observations
• single-source speculation
Confidence_Level must consider both:
• Evidence_Density
• Evidence_Source_Tier
Insights based primarily on Tier 4 evidence cannot be classified as Validated regardless of source count.
This rule protects Research Brain from low-quality evidence amplification.
Insight Type Classification
All Research Brain entries must be assigned an Insight Type.
Insight_Type options:
• Tactical Insight
• Structural Model
• Strategic Principle
Definitions:
Tactical Insight
Specific operational improvement or tactic.
Examples: hook style, funnel variation, landing page technique.
Structural Model
Framework explaining how a system behaves over time.
Examples: lifecycle models, forecasting models, capital allocation frameworks.
Strategic Principle
High-level rule governing decision-making or system architecture.
Examples: survivability rules, capital discipline, governance frameworks.
This classification ensures insights are stored and interpreted at the correct abstraction level.
Operational Brains must not treat Structural Models or Strategic Principles as tactical instructions.
Experiment Logging Transfer Rule
Current state:
Affiliate Brain owns experiment logging.
Transition state:
Affiliate Brain may log experiments, but:
• all hypotheses must reference an Insight_ID
• all outcomes must update Research Brain records
Future state (Phase 2 Activation):
Research Brain becomes the primary logging authority.
Affiliate Brain becomes execution layer only.
Win/Loss Intelligence Integration
Research Brain owns:
• quantitative win/loss surveys
• qualitative win/loss interviews
• competitor displacement data
• refund pattern mapping
• mechanism rejection mapping
• angle fatigue detection
Operational Brains must submit post-test learning within 48 hours.
Failure to submit triggers a SIT drift alert.
Competitive Intelligence Layer
Research Brain tracks:
Maximum 5 primary competitors per domain.
For each competitor, log:
• positioning shifts
• offer structure changes
• pricing changes
• funnel updates
• traffic channel expansion
• market movement signals
All updates must be logged with timestamp.
Pattern Detection Protocol
Quarterly meta-analysis is mandatory.
Research Brain must:
• cluster recurring Theme_Tags
• detect cross-domain overlap
• flag repeated failure categories
• identify rising mechanisms
• identify declining mechanisms
• detect saturation signals
Output:
Research Pattern Report
This report is delivered to HeadOffice.
Market Opportunity Mapping
Research Brain maintains a Market Opportunity Heatmap.
The Opportunity Heatmap identifies where profitable opportunities are most likely to emerge across monitored markets.
The Heatmap evaluates markets across three dimensions:
• Market Demand
• Monetization Strength
• Attention Density
The intersection of these dimensions produces identifiable opportunity zones.
Opportunity zones include:
Opportunity Hot Zone
High demand, high monetization, high attention.
Emerging Opportunity Zone
High demand, high monetization, low attention.
Content Opportunity Zone
High demand, high attention, low monetization.
Low Opportunity Zone
Low demand, low monetization, low attention.
Research Brain uses the Opportunity Heatmap to:
• prioritize research effort
• detect emerging niches
• detect early market shifts
• guide opportunity discovery
Signals discovered within Heatmap zones may populate the Affiliate Brain Opportunity Queue.
The Heatmap identifies where to search.
Operational Brains determine what to test.
Governance Enforcement
Failure to log research:
• blocks Stage 4 progression
• blocks scaling
• triggers SIT drift alert
No research entry may be deleted.
Archive only.
No retroactive editing of outcome records.
Transition Plan (Controlled Crossover)
Phase 1 – Now / Hybrid State
• Affiliate and PPL continue logging
• Research Brain mirrors and centralizes
• Insight_ID becomes mandatory across domains
Phase 2 – Stabilized State
• Research Brain becomes primary logging layer
• Operational Brains reference only
Phase 3 – Full Maturity
• Research Brain performs automated signal clustering
• cross-brain pattern detection activated
Core Principle
Research Brain exists to prevent:
• emotional decision-making
• repeated failed experiments
• untracked assumptions
• forgotten lessons
• intelligence fragmentation
Consistency > Brilliance
Structure > Instinct
Drift Protection
The system must prevent:
• high-confidence claims being made without Research linkage
• Tier 4 evidence being amplified into false certainty
• operational Brains treating research summaries as direct execution approval
• research records being retroactively rewritten to fit outcomes
• experiment learning failing to return to originating insights
• intelligence existing only in conversation instead of structured records
Research intelligence must remain cumulative, linked, and auditable.
Architectural Intent
Research Brain Canon exists to make MWMS intelligence disciplined, cumulative, and structurally trustworthy.
Its role is to ensure that insights are captured with evidence quality, interpreted at the correct level of abstraction, linked to experiments and outcomes, and preserved as a reusable intelligence layer beneath all operational decision systems.
Final Rule
Research may inform action, but it may never become action authority.
If intelligence is not validated, classified, linked, and logged, it is not strong enough to govern MWMS decisions.
Change Log
Version: v1.5
Date: 2026-03-15
Author: MWMS HeadOffice
Change: Standardised the page fully to the locked cleanup format for this pass. Preserved all governing logic including structural positioning, authority boundaries, evidence classification, Evidence Source Tier Classification, Insight Type Classification, experiment logging transfer rules, win/loss integration, competitive intelligence, pattern detection, market opportunity mapping, governance enforcement, transition-state rules, and core principle. Added Drift Protection, Architectural Intent, Final Rule, and updated the review date.
Version: v1.4
Date: 2026-03-14
Author: MWMS HeadOffice
Change: Rebuilt Research Brain Canon to align with MWMS document standards. Added Document Type header, formalised Purpose / Scope / Definition / Rules structure, added Parent field, normalised section formatting, and preserved all governing logic including evidence classification, insight typing, market opportunity mapping, and transfer-state rules.
Version: v1.3
Date: 2026-03-09
Author: HeadOffice
Change: Introduced Evidence Source Tier Classification system to distinguish evidence reliability levels and improve confidence evaluation integrity.
Version: v1.2
Date: 2026-03-09
Author: HeadOffice
Change: Introduced Market Opportunity Mapping layer and Opportunity Heatmap framework to guide systematic opportunity discovery and feed signals into Affiliate Brain Opportunity Queue.
Version: v1.1
Date: 2026-03-09
Author: HeadOffice
Change: Introduced Insight Type Classification system to distinguish Tactical Insights, Structural Models, and Strategic Principles within Research Brain records.
Version: v1.0
Date: Prior entry preserved
Author: HeadOffice
Change: Initial canon structure established.
END – RESEARCH BRAIN CANON v1.5