feat(master-reference): MREF-F500-WP-013 — Enterprise AI Governance Master Reference 2026-2030 for Fortune 500#44
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…Architecture, Safety & Global Regulation Master Reference 2026-2030 Adds the capstone master reference document consolidating all 12 prior whitepapers (WP-001 through WP-012) and 5 technical specifications into a single authoritative resource for Fortune 500 executive leadership, board committees, regulators, and enterprise architecture teams. New files: - docs/reports/ENTERPRISE_AI_GOVERNANCE_MASTER_REFERENCE.md (767 lines, 12 sections) - rag-agentic-dashboard/public/master-reference.html (68KB interactive dashboard, 12 tabs) Modified: - rag-agentic-dashboard/server.js (MASTER_REFERENCE data object + 27 API endpoints) Nine domains covered: 1. Sentinel AI Governance Platform v2.4 — 22 systems, 847 rules, 1.2M eval/day, 4.2ms P99 2. EAIP Agent Interoperability Protocol — 10,400 RPC/s, SPIFFE identity, 99.97% handoff 3. WorkflowAI Pro Orchestration — 12,000 workflows/day, 7-stage LLMOps pipeline 4. Self-Multiplying AI Systems — 12-dimension risk taxonomy, ARS 55.8→74.3, kill-switch 50-280ms 5. Tiered Admin vs Autonomous Agents — $14.8M ESAE reconciliation, MTTR 47min→<3min 6. Cognitive Orchestrator — CAIO role, Board AI Subcommittee, 3-tier authority matrix 7. Global Regulation — 16+ frameworks, 278 OPA rules, 88.4% compliance, 4-tier escalation 8. Enterprise AI Security — 7-layer defence-in-depth, 8-class STRIDE+AI threat model 9. Technical Specifications — OPA Rego, MVAGS (48hr/$2.4K/mo), CRP v1.0, 7 CI/CD gates Investment: $57.6M 5-year | NPV $96.2M | IRR 39.8% | Payback 2.3yr Regression: 129 endpoints tested, 129 passed, 0 failures
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Review these changes at https://app.gitnotebooks.com/OneFineStarstuff/OneFineStarstuff.github.io/pull/44 |
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Reviewer's GuideAdds a new enterprise AI governance master reference document (WP-013), an accompanying 12-tab interactive dashboard, and a MASTER_REFERENCE data model plus 27 REST endpoints to expose the reference content via the existing rag-agentic-dashboard server. Sequence diagram for dashboard loading MASTER_REFERENCE data via new API endpointssequenceDiagram
actor User
participant Browser
participant DashboardHTML as master_reference_html
participant Server as ExpressServer
participant Model as MASTER_REFERENCE
User->>Browser: Navigate to /master-reference.html
Browser->>DashboardHTML: Load HTML, CSS, JS
DashboardHTML->>Server: HTTP GET /api/master-reference/summary
Server->>Model: Read meta, investment, keyMetrics, recommendations
Model-->>Server: Summary payload
Server-->>DashboardHTML: 200 JSON summary
DashboardHTML-->>Browser: Render Overview tab (KPIs, domains, investment)
User->>Browser: Click Sentinel v2_4 tab
Browser->>DashboardHTML: Activate Sentinel panel
DashboardHTML->>Server: HTTP GET /api/master-reference/sentinel
Server->>Model: Read sentinel
Model-->>Server: Sentinel section
Server-->>DashboardHTML: 200 JSON sentinel
DashboardHTML-->>Browser: Render Sentinel metrics and tables
User->>Browser: Click EAIP tab
Browser->>DashboardHTML: Activate EAIP panel
DashboardHTML->>Server: HTTP GET /api/master-reference/eaip/protocols
Server->>Model: Read eaip.protocols and eaip.handoff
Model-->>Server: Protocols + handoff
Server-->>DashboardHTML: 200 JSON protocols
DashboardHTML-->>Browser: Render EAIP tri_plane architecture
User->>Browser: Click Investment tab
Browser->>DashboardHTML: Activate Investment panel
DashboardHTML->>Server: HTTP GET /api/master-reference/investment
Server->>Model: Read investment
Model-->>Server: Investment section
Server-->>DashboardHTML: 200 JSON investment
DashboardHTML-->>Browser: Render ROI tables and charts
Class diagram for MASTER_REFERENCE data model and API payloadsclassDiagram
class MASTER_REFERENCE {
+meta Meta
+sentinel Sentinel
+eaip EAIP
+workflowAI WorkflowAI
+selfMultiplying SelfMultiplying
+tieredAdmin TieredAdmin
+cognitiveOrchestrator CognitiveOrchestrator
+globalRegulation GlobalRegulation
+security SecurityDomain
+technicalSpecs TechnicalSpecs
+investment Investment
+recommendations string[]
+keyMetrics KeyMetrics
}
class Meta {
+docRef string
+title string
+subtitle string
+suiteId string
+version string
+date string
+classification string
+authors string[]
+audience string[]
+companionDocs string
+sections number
+domains number
+totalFrameworks number
+jurisdictions number
+investmentTotal string
+npv string
+irr string
+payback string
}
class Sentinel {
+title string
+abstract string
+components SentinelComponent[]
+ruleCategories SentinelRuleCategory[]
+metrics SentinelMetrics
+roadmap SentinelRoadmapVersion[]
}
class SentinelComponent {
+name string
+version string
+function string
+metric string
}
class SentinelRuleCategory {
+category string
+rules number
+framework string
}
class SentinelMetrics {
+systemsGoverned number
+rules number
+dailyEvals string
+p99 string
+availability string
+domains number
+detectionToResponse string
}
class SentinelRoadmapVersion {
+version string
+status string
+target string
+stages string
}
class EAIP {
+title string
+abstract string
+fragmentation EAIPFragmentation
+protocols EAIPProtocol[]
+handoff EAIPHandoff
+spiffe EAIPSPIFFE
+deployment EAIPDeployment
}
class EAIPFragmentation {
+totalAnnualCost number
+categories EAIPFragmentCategory[]
}
class EAIPFragmentCategory {
+name string
+annual number
}
class EAIPProtocol {
+plane string
+protocol string
+latency string
+throughput string
+auth string
}
class EAIPHandoff {
+reliability string
+p99 string
+p50 string
+phases string[]
}
class EAIPSPIFFE {
+rotationInterval string
+attestation string
+invariant string
}
class EAIPDeployment {
+totalInvestment number
+paybackMonths number
+phases number
}
class WorkflowAI {
+title string
+abstract string
+metrics WorkflowMetrics
+llmOpsStages LlmOpsStage[]
}
class WorkflowMetrics {
+dailyWorkflows number
+completionRate string
+availability string
+meanRecovery string
+monitoringPoints number
+costPerWorkflow string
}
class LlmOpsStage {
+stage number
+name string
+gate string
}
class SelfMultiplying {
+title string
+abstract string
+riskDimensions number
+currentARS number
+projectedARS number
+overallMitigation string
+killSwitch KillSwitch
+agentRegistry AgentRegistry
+sentinelRules string[]
+cardinalInvariant string
}
class KillSwitch {
+software string
+hsm string
+network string
}
class AgentRegistry {
+maxConcurrent number
+lifetimeBound string
+scopeReview string
+baselinePeriod string
}
class TieredAdmin {
+title string
+abstract string
+investment number
+duration string
+phases TieredPhase[]
+outcomes TieredOutcomes
+fintech TieredFintechContext
+cardinalInvariant string
}
class TieredPhase {
+phase number
+name string
+years string
+investment number
+focus string
}
class TieredOutcomes {
+mttrReduction string
+autonomousRemediation string
+socRecovery string
+certifications string[]
}
class TieredFintechContext {
+transactionVolume string
+accounts string
+agents number
+infrastructure string
}
class CognitiveOrchestrator {
+title string
+abstract string
+caio CAIORole
+deploymentAuthority DeploymentAuthorityEntry[]
+boardSubcommittee BoardSubcommittee
+tabletopExercises string[]
+maturity CognitiveMaturity
+investment CognitiveInvestment
}
class CAIORole {
+title string
+reportsTo string
+authority string
+notSubordinatedTo string
}
class DeploymentAuthorityEntry {
+tier number
+riskLevel string
+approver string
+responseTime string
}
class BoardSubcommittee {
+composition string
+cadence string
+decisionRights string
}
class CognitiveMaturity {
+current number
+currentName string
+target number
+targetName string
+targetDate string
}
class CognitiveInvestment {
+total number
+breakdown CognitiveInvestmentItem[]
}
class CognitiveInvestmentItem {
+category string
+cost number
}
class GlobalRegulation {
+title string
+abstract string
+frameworks RegulationFramework[]
+totalOpaRules number
+overallScore number
+overallTarget number
+icgc ICGCMeta
+escalationTiers number
}
class RegulationFramework {
+name string
+opaRules number
+score number
+target string
+jurisdiction string
}
class ICGCMeta {
+components number
+gcrApiEndpoints number
+status string
+timeline string
}
class SecurityDomain {
+title string
+abstract string
+layers SecurityLayer[]
+threats string[]
}
class SecurityLayer {
+layer string
+tech string
+metric string
}
class TechnicalSpecs {
+title string
+abstract string
+opaRuleGroups number
+totalRules number
+mvags MVAGS
+crp CRP
+cicdGates number
+architectures ReferenceArchitecture[]
}
class MVAGS {
+deployTime string
+monthlyCost number
+components number
}
class CRP {
+version string
+dimensions number
+thresholds string[]
}
class ReferenceArchitecture {
+name string
+throughput string
+governance string
}
class Investment {
+totalFiveYear number
+npv number
+irr number
+payback number
+currency string
+domains InvestmentDomain[]
+annualSavings number
+steadyStateCost number
}
class InvestmentDomain {
+domain string
+cost number
+npv number
+irr number
+payback number
}
class KeyMetrics {
+sections number
+domains number
+frameworks number
+opaRules number
+sentinelRules number
+systemsGoverned number
+dailyEvals string
+p99Latency string
+eaipRpcPerSec number
+handoffReliability string
+workflowsPerDay number
+ragAccuracy string
+riskDimensions number
+agentRiskScore number
+killSwitchLatency string
+securityLayers number
+threatClasses number
+crpDimensions number
+fiveYearInvestment string
+npv string
+irr string
+payback string
+maturityCheckpoints number
+deploymentPhases number
+cicdGates number
+referenceArchitectures number
}
MASTER_REFERENCE --> Meta
MASTER_REFERENCE --> Sentinel
MASTER_REFERENCE --> EAIP
MASTER_REFERENCE --> WorkflowAI
MASTER_REFERENCE --> SelfMultiplying
MASTER_REFERENCE --> TieredAdmin
MASTER_REFERENCE --> CognitiveOrchestrator
MASTER_REFERENCE --> GlobalRegulation
MASTER_REFERENCE --> SecurityDomain
MASTER_REFERENCE --> TechnicalSpecs
MASTER_REFERENCE --> Investment
MASTER_REFERENCE --> KeyMetrics
Sentinel --> SentinelComponent
Sentinel --> SentinelRuleCategory
Sentinel --> SentinelMetrics
Sentinel --> SentinelRoadmapVersion
EAIP --> EAIPFragmentation
EAIP --> EAIPProtocol
EAIP --> EAIPHandoff
EAIP --> EAIPSPIFFE
EAIP --> EAIPDeployment
EAIPFragmentation --> EAIPFragmentCategory
WorkflowAI --> WorkflowMetrics
WorkflowAI --> LlmOpsStage
SelfMultiplying --> KillSwitch
SelfMultiplying --> AgentRegistry
TieredAdmin --> TieredPhase
TieredAdmin --> TieredOutcomes
TieredAdmin --> TieredFintechContext
CognitiveOrchestrator --> CAIORole
CognitiveOrchestrator --> DeploymentAuthorityEntry
CognitiveOrchestrator --> BoardSubcommittee
CognitiveOrchestrator --> CognitiveMaturity
CognitiveOrchestrator --> CognitiveInvestment
CognitiveInvestment --> CognitiveInvestmentItem
GlobalRegulation --> RegulationFramework
GlobalRegulation --> ICGCMeta
SecurityDomain --> SecurityLayer
TechnicalSpecs --> MVAGS
TechnicalSpecs --> CRP
TechnicalSpecs --> ReferenceArchitecture
Investment --> InvestmentDomain
File-Level Changes
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Hey - I've found 5 issues, and left some high level feedback:
- The MASTER_REFERENCE object embeds a very large amount of static, domain data directly in server.js; consider moving this into a separate JSON/config module so the API layer remains lean and easier to maintain.
- Key metrics and domain values (e.g., 278 OPA rules, $57.6M investment, NPV/IRR figures) are duplicated across server.js, the HTML dashboard, and the Markdown report; introducing a single source of truth for these constants would reduce drift risk and simplify updates.
- The master-reference.html currently hardcodes all content rather than consuming the new /api/master-reference endpoints; wiring the dashboard to the API would improve reuse of the data model and ensure the UI reflects API changes automatically.
Prompt for AI Agents
Please address the comments from this code review:
## Overall Comments
- The MASTER_REFERENCE object embeds a very large amount of static, domain data directly in server.js; consider moving this into a separate JSON/config module so the API layer remains lean and easier to maintain.
- Key metrics and domain values (e.g., 278 OPA rules, $57.6M investment, NPV/IRR figures) are duplicated across server.js, the HTML dashboard, and the Markdown report; introducing a single source of truth for these constants would reduce drift risk and simplify updates.
- The master-reference.html currently hardcodes all content rather than consuming the new /api/master-reference endpoints; wiring the dashboard to the API would improve reuse of the data model and ensure the UI reflects API changes automatically.
## Individual Comments
### Comment 1
<location path="rag-agentic-dashboard/server.js" line_range="9161" />
<code_context>
+app.get('/api/master-reference/meta', (_, res) => res.json(MASTER_REFERENCE.meta));
+app.get('/api/master-reference/sentinel', (_, res) => res.json(MASTER_REFERENCE.sentinel));
+app.get('/api/master-reference/sentinel/components', (_, res) => res.json({ components: MASTER_REFERENCE.sentinel.components }));
+app.get('/api/master-reference/sentinel/rules', (_, res) => res.json({ categories: MASTER_REFERENCE.sentinel.ruleCategories, total: 278 }));
+app.get('/api/master-reference/sentinel/roadmap', (_, res) => res.json({ versions: MASTER_REFERENCE.sentinel.roadmap }));
+app.get('/api/master-reference/eaip', (_, res) => res.json(MASTER_REFERENCE.eaip));
</code_context>
<issue_to_address>
**suggestion (bug_risk):** Avoid hardcoding the total rule count; derive it from the data to prevent drift.
Since this value is already implied by `MASTER_REFERENCE.sentinel.ruleCategories` and used elsewhere, it may easily drift if categories or counts change. Consider deriving it instead, for example:
```ts
const total = MASTER_REFERENCE.sentinel.ruleCategories
.reduce((sum, c) => sum + c.rules, 0);
```
and returning that, or storing a single `totalOpaRules` field on `MASTER_REFERENCE.sentinel` and using it here.
```suggestion
app.get('/api/master-reference/sentinel/rules', (_, res) => {
const { ruleCategories } = MASTER_REFERENCE.sentinel;
const total = ruleCategories.reduce((sum, c) => sum + (c.rules ?? 0), 0);
return res.json({ categories: ruleCategories, total });
});
```
</issue_to_address>
### Comment 2
<location path="rag-agentic-dashboard/public/master-reference.html" line_range="131-118" />
<code_context>
+ </div>
+</div>
+
+<div class="tabs" id="tabs">
+ <div class="tab active" data-tab="overview">Overview</div>
+ <div class="tab" data-tab="sentinel">Sentinel v2.4</div>
+ <div class="tab" data-tab="eaip">EAIP</div>
+ <div class="tab" data-tab="workflow">WorkflowAI Pro</div>
+ <div class="tab" data-tab="selfmult">Self-Multiplying AI</div>
+ <div class="tab" data-tab="tiered">Tiered Admin</div>
+ <div class="tab" data-tab="cognitive">Cognitive Orchestrator</div>
+ <div class="tab" data-tab="regulation">Global Regulation</div>
+ <div class="tab" data-tab="security">Security</div>
+ <div class="tab" data-tab="techspec">Technical Specs</div>
+ <div class="tab" data-tab="investment">Investment & ROI</div>
+ <div class="tab" data-tab="roadmap">Roadmap</div>
+</div>
+
+<!-- ════════════════════ OVERVIEW ════════════════════ -->
</code_context>
<issue_to_address>
**suggestion:** Tabs are implemented with plain divs and clicks, which may cause accessibility issues; consider using semantic elements and ARIA roles.
Using non-interactive `<div>` elements with click handlers makes the tabs hard to use with screen readers and keyboards. Consider switching to `<button>` for each tab and applying `role="tablist"`, `role="tab"`, and `role="tabpanel"` with `aria-selected` and keyboard focus/arrow-key handling to support assistive technologies while preserving the current look.
Suggested implementation:
```
<div class="tabs" id="tabs" role="tablist" aria-label="Master reference sections">
<button
class="tab active"
id="tab-overview"
type="button"
role="tab"
aria-selected="true"
aria-controls="panel-overview"
tabindex="0"
data-tab="overview"
>
Overview
</button>
<button
class="tab"
id="tab-sentinel"
type="button"
role="tab"
aria-selected="false"
aria-controls="panel-sentinel"
tabindex="-1"
data-tab="sentinel"
>
Sentinel v2.4
</button>
<button
class="tab"
id="tab-eaip"
type="button"
role="tab"
aria-selected="false"
aria-controls="panel-eaip"
tabindex="-1"
data-tab="eaip"
>
EAIP
</button>
<button
class="tab"
id="tab-workflow"
type="button"
role="tab"
aria-selected="false"
aria-controls="panel-workflow"
tabindex="-1"
data-tab="workflow"
>
WorkflowAI Pro
</button>
<button
class="tab"
id="tab-selfmult"
type="button"
role="tab"
aria-selected="false"
aria-controls="panel-selfmult"
tabindex="-1"
data-tab="selfmult"
>
Self-Multiplying AI
</button>
<button
class="tab"
id="tab-tiered"
type="button"
role="tab"
aria-selected="false"
aria-controls="panel-tiered"
tabindex="-1"
data-tab="tiered"
>
Tiered Admin
</button>
<button
class="tab"
id="tab-cognitive"
type="button"
role="tab"
aria-selected="false"
aria-controls="panel-cognitive"
tabindex="-1"
data-tab="cognitive"
>
Cognitive Orchestrator
</button>
<button
class="tab"
id="tab-regulation"
type="button"
role="tab"
aria-selected="false"
aria-controls="panel-regulation"
tabindex="-1"
data-tab="regulation"
>
Global Regulation
</button>
<button
class="tab"
id="tab-security"
type="button"
role="tab"
aria-selected="false"
aria-controls="panel-security"
tabindex="-1"
data-tab="security"
>
Security
</button>
<button
class="tab"
id="tab-techspec"
type="button"
role="tab"
aria-selected="false"
aria-controls="panel-techspec"
tabindex="-1"
data-tab="techspec"
>
Technical Specs
</button>
<button
class="tab"
id="tab-investment"
type="button"
role="tab"
aria-selected="false"
aria-controls="panel-investment"
tabindex="-1"
data-tab="investment"
>
Investment & ROI
</button>
<button
class="tab"
id="tab-roadmap"
type="button"
role="tab"
aria-selected="false"
aria-controls="panel-roadmap"
tabindex="-1"
data-tab="roadmap"
>
Roadmap
</button>
</div>
```
```
<!-- ════════════════════ OVERVIEW ════════════════════ -->
<div
class="panel active"
id="panel-overview"
role="tabpanel"
aria-labelledby="tab-overview"
tabindex="0"
>
```
1. Ensure each corresponding panel (`panel-sentinel`, `panel-eaip`, `panel-workflow`, etc.) is given `role="tabpanel"` and `aria-labelledby="tab-..."` pointing to its tab id, and is not focusable (`tabindex="-1"`) when inactive.
2. Update the tab-switching JavaScript so that when a tab is activated it:
- Sets `aria-selected="true"` and `tabindex="0"` on the active tab and `aria-selected="false"` / `tabindex="-1"` on all others.
- Moves focus to the newly activated tab when triggered by keyboard.
3. Add keyboard support on the tab buttons:
- `Enter` / `Space` activate a tab (you may already get this for free with `<button>`).
- Left/Right arrow keys move focus to the previous/next tab within the `role="tablist"` without activating it (or optionally activating on focus, depending on your desired pattern).
</issue_to_address>
### Comment 3
<location path="docs/reports/ENTERPRISE_AI_GOVERNANCE_MASTER_REFERENCE.md" line_range="583" />
<code_context>
+| Explainability | 30 | EU AI Act Art. 13 | `explanation_generated` |
+| **Total** | **278** | **16 frameworks** | |
+
+### 10.2 MVAGS --- Minimal Viable AGI Governance Stack
+
+| Component | Technology | Deploy Time | Monthly Cost |
</code_context>
<issue_to_address>
**suggestion (typo):** Consider changing "Minimal Viable" to the more standard "Minimum Viable" in the MVAGS heading.
Using the standard phrase here (e.g., “Minimum Viable AGI Governance Stack”) will keep terminology consistent with common usage like “Minimum Viable Product.”
```suggestion
### 10.2 MVAGS --- Minimum Viable AGI Governance Stack
```
</issue_to_address>
### Comment 4
<location path="docs/reports/ENTERPRISE_AI_GOVERNANCE_MASTER_REFERENCE.md" line_range="305-314" />
<code_context>
+- **Behavioral baseline**: 30-day baseline with continuous drift monitoring
</code_context>
<issue_to_address>
**suggestion (typo):** Spelling of "behaviour/behavior" is inconsistent; consider standardising on one variant across the document.
This line uses the US form (“Behavioral baseline”), while later sections use UK forms (“endpoint behaviour”, “behavioural risk scoring”). Given the other British spellings in the document, consider updating this to match the chosen convention.
Suggested implementation:
```
- **Scope declaration**: Explicit resource access manifest reviewed by VP AI Safety
- **Behavioural baseline**: 30-day baseline with continuous drift monitoring
- **Replication authorization**: Explicit approval for any agent spawning sub-agents
```
```
| SEN-AGENT-002 | `cross_tier_deny` | Cross-Boundary | Behavioural sidecar + anomaly detection |
```
To fully implement consistent spelling across the document:
1. Search the entire docs/reports/ENTERPRISE_AI_GOVERNANCE_MASTER_REFERENCE.md for the substrings "Behavior", "behavior", and "Behavioral".
2. Where contextually appropriate, update them to "Behaviour" / "behaviour" / "Behavioural" to match the British spelling convention already used (e.g., "behavioural risk scoring", "Emergent Behaviour").
3. Similarly, confirm there are no remaining US spellings ("authorization", "standardization", etc.) if the style guide prefers consistent British English for the whole document.
</issue_to_address>
### Comment 5
<location path="docs/reports/ENTERPRISE_AI_GOVERNANCE_MASTER_REFERENCE.md" line_range="674" />
<code_context>
+The total recommended investment across all governance, security, interoperability, and organisational transformation domains is $57.6M over 60 months, with projected NPV of $96.2M at 10% discount rate, IRR of 39.8%, payback period of 2.3 years, and risk-adjusted BCR of 2.67x. Steady-state annual savings of $28.6M derive from regulatory finding reduction (68%, $12.4M), audit preparation reduction (78%, $4.8M), operational efficiency (23%, $8.2M), incident cost reduction (54%, $6.1M), insurance premium reduction ($1.8M), reputational risk avoidance ($8.0M expected value), EAIP integration savings ($4.2M), and security automation ($2.4M annualised).
</code_context>
<issue_to_address>
**question (bug_risk):** Steady-state annual savings are inconsistent between the abstract ($28.6M) and the detailed table ($47.9M).
Section 11’s abstract lists steady-state annual savings of $28.6M, while the line-item totals in 11.2 add up to $47.9M. Please reconcile or clearly distinguish these amounts so there is a single, unambiguous steady-state savings figure.
</issue_to_address>Help me be more useful! Please click 👍 or 👎 on each comment and I'll use the feedback to improve your reviews.
| app.get('/api/master-reference/meta', (_, res) => res.json(MASTER_REFERENCE.meta)); | ||
| app.get('/api/master-reference/sentinel', (_, res) => res.json(MASTER_REFERENCE.sentinel)); | ||
| app.get('/api/master-reference/sentinel/components', (_, res) => res.json({ components: MASTER_REFERENCE.sentinel.components })); | ||
| app.get('/api/master-reference/sentinel/rules', (_, res) => res.json({ categories: MASTER_REFERENCE.sentinel.ruleCategories, total: 278 })); |
There was a problem hiding this comment.
suggestion (bug_risk): Avoid hardcoding the total rule count; derive it from the data to prevent drift.
Since this value is already implied by MASTER_REFERENCE.sentinel.ruleCategories and used elsewhere, it may easily drift if categories or counts change. Consider deriving it instead, for example:
const total = MASTER_REFERENCE.sentinel.ruleCategories
.reduce((sum, c) => sum + c.rules, 0);and returning that, or storing a single totalOpaRules field on MASTER_REFERENCE.sentinel and using it here.
Suggested change
| app.get('/api/master-reference/sentinel/rules', (_, res) => res.json({ categories: MASTER_REFERENCE.sentinel.ruleCategories, total: 278 })); | |
| app.get('/api/master-reference/sentinel/rules', (_, res) => { | |
| const { ruleCategories } = MASTER_REFERENCE.sentinel; | |
| const total = ruleCategories.reduce((sum, c) => sum + (c.rules ?? 0), 0); | |
| return res.json({ categories: ruleCategories, total }); | |
| }); |
| <div class="header-top"> | ||
| <span class="doc-ref">MREF-F500-WP-013 v1.0.0</span> | ||
| <span class="classification">CONFIDENTIAL</span> | ||
| </div> |
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suggestion: Tabs are implemented with plain divs and clicks, which may cause accessibility issues; consider using semantic elements and ARIA roles.
Using non-interactive <div> elements with click handlers makes the tabs hard to use with screen readers and keyboards. Consider switching to <button> for each tab and applying role="tablist", role="tab", and role="tabpanel" with aria-selected and keyboard focus/arrow-key handling to support assistive technologies while preserving the current look.
Suggested implementation:
<div class="tabs" id="tabs" role="tablist" aria-label="Master reference sections">
<button
class="tab active"
id="tab-overview"
type="button"
role="tab"
aria-selected="true"
aria-controls="panel-overview"
tabindex="0"
data-tab="overview"
>
Overview
</button>
<button
class="tab"
id="tab-sentinel"
type="button"
role="tab"
aria-selected="false"
aria-controls="panel-sentinel"
tabindex="-1"
data-tab="sentinel"
>
Sentinel v2.4
</button>
<button
class="tab"
id="tab-eaip"
type="button"
role="tab"
aria-selected="false"
aria-controls="panel-eaip"
tabindex="-1"
data-tab="eaip"
>
EAIP
</button>
<button
class="tab"
id="tab-workflow"
type="button"
role="tab"
aria-selected="false"
aria-controls="panel-workflow"
tabindex="-1"
data-tab="workflow"
>
WorkflowAI Pro
</button>
<button
class="tab"
id="tab-selfmult"
type="button"
role="tab"
aria-selected="false"
aria-controls="panel-selfmult"
tabindex="-1"
data-tab="selfmult"
>
Self-Multiplying AI
</button>
<button
class="tab"
id="tab-tiered"
type="button"
role="tab"
aria-selected="false"
aria-controls="panel-tiered"
tabindex="-1"
data-tab="tiered"
>
Tiered Admin
</button>
<button
class="tab"
id="tab-cognitive"
type="button"
role="tab"
aria-selected="false"
aria-controls="panel-cognitive"
tabindex="-1"
data-tab="cognitive"
>
Cognitive Orchestrator
</button>
<button
class="tab"
id="tab-regulation"
type="button"
role="tab"
aria-selected="false"
aria-controls="panel-regulation"
tabindex="-1"
data-tab="regulation"
>
Global Regulation
</button>
<button
class="tab"
id="tab-security"
type="button"
role="tab"
aria-selected="false"
aria-controls="panel-security"
tabindex="-1"
data-tab="security"
>
Security
</button>
<button
class="tab"
id="tab-techspec"
type="button"
role="tab"
aria-selected="false"
aria-controls="panel-techspec"
tabindex="-1"
data-tab="techspec"
>
Technical Specs
</button>
<button
class="tab"
id="tab-investment"
type="button"
role="tab"
aria-selected="false"
aria-controls="panel-investment"
tabindex="-1"
data-tab="investment"
>
Investment & ROI
</button>
<button
class="tab"
id="tab-roadmap"
type="button"
role="tab"
aria-selected="false"
aria-controls="panel-roadmap"
tabindex="-1"
data-tab="roadmap"
>
Roadmap
</button>
</div>
<!-- ════════════════════ OVERVIEW ════════════════════ -->
<div
class="panel active"
id="panel-overview"
role="tabpanel"
aria-labelledby="tab-overview"
tabindex="0"
>
- Ensure each corresponding panel (
panel-sentinel,panel-eaip,panel-workflow, etc.) is givenrole="tabpanel"andaria-labelledby="tab-..."pointing to its tab id, and is not focusable (tabindex="-1") when inactive. - Update the tab-switching JavaScript so that when a tab is activated it:
- Sets
aria-selected="true"andtabindex="0"on the active tab andaria-selected="false"/tabindex="-1"on all others. - Moves focus to the newly activated tab when triggered by keyboard.
- Sets
- Add keyboard support on the tab buttons:
Enter/Spaceactivate a tab (you may already get this for free with<button>).- Left/Right arrow keys move focus to the previous/next tab within the
role="tablist"without activating it (or optionally activating on focus, depending on your desired pattern).
| | Explainability | 30 | EU AI Act Art. 13 | `explanation_generated` | | ||
| | **Total** | **278** | **16 frameworks** | | | ||
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| ### 10.2 MVAGS --- Minimal Viable AGI Governance Stack |
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suggestion (typo): Consider changing "Minimal Viable" to the more standard "Minimum Viable" in the MVAGS heading.
Using the standard phrase here (e.g., “Minimum Viable AGI Governance Stack”) will keep terminology consistent with common usage like “Minimum Viable Product.”
Suggested change
| ### 10.2 MVAGS --- Minimal Viable AGI Governance Stack | |
| ### 10.2 MVAGS --- Minimum Viable AGI Governance Stack |
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| - **Behavioral baseline**: 30-day baseline with continuous drift monitoring | ||
| - **Replication authorization**: Explicit approval for any agent spawning sub-agents | ||
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| ### 5.4 Sentinel-OPA Control Pairs | ||
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| | Sentinel Rule | OPA Rule | Risk | Primary Control | | ||
| |--------------|---------|------|-----------------| | ||
| | SEN-AGENT-001 | `agent_scope_limit` | Autonomous Decision | 15-min TTL auth tokens | | ||
| | SEN-AGENT-002 | `cross_tier_deny` | Cross-Boundary | Behavioral sidecar + anomaly detection | | ||
| | SEN-AGENT-003 | `goal_drift_check` | Goal Misspecification | CRP alignment scoring | |
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suggestion (typo): Spelling of "behaviour/behavior" is inconsistent; consider standardising on one variant across the document.
This line uses the US form (“Behavioral baseline”), while later sections use UK forms (“endpoint behaviour”, “behavioural risk scoring”). Given the other British spellings in the document, consider updating this to match the chosen convention.
Suggested implementation:
- **Scope declaration**: Explicit resource access manifest reviewed by VP AI Safety
- **Behavioural baseline**: 30-day baseline with continuous drift monitoring
- **Replication authorization**: Explicit approval for any agent spawning sub-agents
| SEN-AGENT-002 | `cross_tier_deny` | Cross-Boundary | Behavioural sidecar + anomaly detection |
To fully implement consistent spelling across the document:
- Search the entire docs/reports/ENTERPRISE_AI_GOVERNANCE_MASTER_REFERENCE.md for the substrings "Behavior", "behavior", and "Behavioral".
- Where contextually appropriate, update them to "Behaviour" / "behaviour" / "Behavioural" to match the British spelling convention already used (e.g., "behavioural risk scoring", "Emergent Behaviour").
- Similarly, confirm there are no remaining US spellings ("authorization", "standardization", etc.) if the style guide prefers consistent British English for the whole document.
| | Security automation | $2.4M | SOC analyst capacity recovery | | ||
| | Insurance premium reduction | $1.8M | AI governance certification discount | | ||
| | Reputational risk avoidance | $8.0M | Probability-weighted brand impact | | ||
| | **Total** | **$47.9M** | | |
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question (bug_risk): Steady-state annual savings are inconsistent between the abstract ($28.6M) and the detailed table ($47.9M).
Section 11’s abstract lists steady-state annual savings of $28.6M, while the line-item totals in 11.2 add up to $47.9M. Please reconcile or clearly distinguish these amounts so there is a single, unambiguous steady-state savings figure.
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MREF-F500-WP-013 — Enterprise AI Governance, Architecture, Safety & Global Regulation: Master Reference 2026-2030
Summary
Capstone master reference document consolidating all 12 prior whitepapers (WP-001 through WP-012) and 5 technical specifications into a single authoritative resource for Fortune 500 executive leadership, board committees, regulators, and enterprise architecture teams.
Files Changed
docs/reports/ENTERPRISE_AI_GOVERNANCE_MASTER_REFERENCE.mdrag-agentic-dashboard/public/master-reference.htmlrag-agentic-dashboard/server.jsNine Domains Covered
Investment Analysis
Interactive Dashboard Features (12 Tabs)
Overview, Sentinel v2.4, EAIP, WorkflowAI Pro, Self-Multiplying AI, Tiered Admin, Cognitive Orchestrator, Global Regulation, Security, Technical Specs, Investment & ROI, Implementation Roadmap
API Endpoints (27 New)
/api/master-referenceand sub-routes covering sentinel, eaip, workflow, self-multiplying, tiered-admin, cognitive-orchestrator, global-regulation, security, technical-specs, investment, recommendations, metrics, and summary.Testing
Document Format
Professional Markdown with
<title>,<abstract>, and<content>XML semantic tags suitable for C-suite, board, regulator, enterprise architecture, AI platform engineering, and research audiences.Summary by Sourcery
Introduce an enterprise AI governance master reference and expose it via a new interactive dashboard and API.
New Features:
Documentation: