Add AGI/ASI Governance Master Reference (2026–2030) — institutional-grade blueprint#61
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Review these changes at https://app.gitnotebooks.com/OneFineStarstuff/OneFineStarstuff.github.io/pull/61 |
Reviewer's GuideAdds a single, very large governance reference markdown document providing an institutional-grade AGI/ASI governance blueprint for 2026–2030, including architecture, controls, templates, metrics, and technical patterns for regulator-ready AI programs. Sequence diagram for Kafka ACL change with policy-as-code CI/CD gatessequenceDiagram
actor Developer
participant GitRepo
participant CI_Pipeline
participant OPA_Engine
participant Terraform_Plans
participant Kafka_Cluster
participant Evidence_Pipeline
Developer->>GitRepo: push_kafka_acl_change
GitRepo-->>CI_Pipeline: trigger_pipeline
CI_Pipeline->>CI_Pipeline: run_lint_and_unit_tests
CI_Pipeline->>Terraform_Plans: generate_plan
Terraform_Plans-->>CI_Pipeline: tfplan_output
CI_Pipeline->>OPA_Engine: evaluate_acl_policy(tfplan_output)
OPA_Engine-->>CI_Pipeline: decision_allow_or_deny
alt policy_decision_allow
CI_Pipeline->>Kafka_Cluster: apply_acl_changes
Kafka_Cluster-->>CI_Pipeline: apply_result
CI_Pipeline->>Evidence_Pipeline: submit_logs(plan_logs, opa_decisions, acl_snapshot)
Evidence_Pipeline-->>CI_Pipeline: evidence_bundle_id
else policy_decision_deny
CI_Pipeline-->>Developer: block_merge_with_violation_details
end
Class diagram for controls, tests, evidence, and AI systemsclassDiagram
class Regulation {
+string id
+string name
+string jurisdiction
}
class Control {
+string control_id
+string statement
+string domain
+string lifecycle_state
}
class Test {
+string test_id
+string control_id
+string type
+string schedule
+string severity_on_fail
}
class EvidenceBundle {
+string bundle_id
+string period
+string signing_key_id
+worm_bucket
+retention_until
}
class AI_System {
+string system_id
+string risk_tier
+string decision_criticality
+string validation_status
}
class GovernanceForum {
+string forum_id
+string name
+string frequency
+string chair_role
}
Regulation "1" -- "*" Control : mandates
Control "1" -- "*" Test : verified_by
Test "1" -- "*" EvidenceBundle : produces
AI_System "1" -- "*" Control : implements
AI_System "1" -- "*" EvidenceBundle : evidenced_by
GovernanceForum "1" -- "*" Control : oversees
GovernanceForum "1" -- "*" AI_System : reviews
Flow diagram for AI incident severity assessment and escalationflowchart LR
Detect["Detect_incident"] --> Classify["Initial_assessment"]
Classify --> ImpactCheck["Assess_impact_legal_scope_novelty"]
ImpactCheck --> ScoreCalc["Compute_incident_score_S"]
ScoreCalc -->|S_ge_critical_threshold| SEV1["Classify_SEV_1"]
ScoreCalc -->|high_le_S_lt_critical| SEV2["Classify_SEV_2"]
ScoreCalc -->|moderate| SEV3["Classify_SEV_3"]
ScoreCalc -->|low| SEV4["Classify_SEV_4"]
SEV1 --> SEV1_Contain["Immediate_containment_and_kill_switch"]
SEV1_Contain --> SEV1_RegNotify["Legal_compliance_regulator_assessment"]
SEV1_RegNotify --> SEV1_Board["Board_notification_le_24h"]
SEV2 --> SEV2_GovCouncil["EAGC_review_le_24h"]
SEV2_GovCouncil --> SEV2_RemPlan["Remediation_plan_le_72h"]
SEV3 --> SEV3_Routine["Routine_governance_review"]
SEV4 --> SEV4_Trend["Trend_analysis_only"]
SEV1_Board --> RCA["Root_cause_analysis"]
SEV2_RemPlan --> RCA
SEV3_Routine --> RCA
SEV4_Trend --> RCA
RCA --> Lessons["Lessons_learned_and_control_uplift"]
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Hey - I've left some high level feedback:
- The single-file document is extremely large and dense; consider splitting it into a few logically scoped documents (e.g., enterprise controls, frontier safety, evidence/assurance) and using a shared index so it’s easier to maintain and navigate over time.
- There is a mix of normative requirements and illustrative examples/templates throughout; adding consistent visual cues (e.g., banners or callouts) and/or an explicit label for each block as “MANDATORY”, “RECOMMENDED”, or “EXAMPLE” would reduce ambiguity for implementers.
Prompt for AI Agents
Please address the comments from this code review:
## Overall Comments
- The single-file document is extremely large and dense; consider splitting it into a few logically scoped documents (e.g., enterprise controls, frontier safety, evidence/assurance) and using a shared index so it’s easier to maintain and navigate over time.
- There is a mix of normative requirements and illustrative examples/templates throughout; adding consistent visual cues (e.g., banners or callouts) and/or an explicit label for each block as “MANDATORY”, “RECOMMENDED”, or “EXAMPLE” would reduce ambiguity for implementers.Help me be more useful! Please click 👍 or 👎 on each comment and I'll use the feedback to improve your reviews.
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💡 Codex Review
Here are some automated review suggestions for this pull request.
Reviewed commit: 926e4bc41d
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Up to standards ✅🟢 Issues
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…-document-86ya7v Signed-off-by: 𝐎𝐧𝐞 𝐅𝐢𝐧𝐞 𝐒𝐭𝐚𝐫𝐬𝐭𝐮𝐟𝐟 <onefinestarstuff@gmail.com>
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💡 Codex Review
Initialize Terraform before generating plan
The workflow example runs terraform ... plan immediately after checkout, but it never initializes the working directory. On a clean CI runner this causes plan to fail before any policy checks run, because Terraform operations that rely on providers/modules/backend require a prior terraform init in the same directory. Add an init step for infra/terraform/envs/nonprod before the plan command.
Run Conftest against the policy namespace
The policy example is declared under package ai.kafka.acl, but the Conftest command does not set --namespace (or --all-namespaces). Conftest defaults to main, so if teams copy these examples as-is, the deny rules in ai.kafka.acl can be skipped and the gate may report success without evaluating the intended ACL policy. Set the namespace explicitly or align package names.
Enforce presence of business purpose on write grants
The rule comment says write access should be denied unless a business-purpose tag is present and approved, but the condition only checks business_purpose_approved and never verifies that business_purpose exists/non-empty. That allows a write grant with approval flag true but no traceable purpose value, weakening the auditability this control is meant to enforce.
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- Open a pull request for review
- Mark a draft as ready
- Comment "@codex review".
If Codex has suggestions, it will comment; otherwise it will react with 👍.
Codex can also answer questions or update the PR. Try commenting "@codex address that feedback".
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Motivation
Description
docs/AGI_ASI_GOVERNANCE_MASTER_REFERENCE_2026_2030.md, a large single-file master reference that includes executive overview, control crosswalks, three-layer compliance model, governance topology, incident escalation, and implementation timelines.Testing
markdownlintand a basic spellcheck pass across the new document to validate formatting and wording and addressed linting findings.Codex Task
Summary by Sourcery
Add a comprehensive AGI/ASI governance master reference document for 2026–2030, providing an institutional-grade blueprint for enterprise AI and frontier safety programs.
Documentation: