{
  "version": "2026-05-three-whitepaper-official-site-publication",
  "generated_at": "2026-05-28",
  "boundary": "Owned-canonical and authored-analysis entity graph for Jearon Wong, MPLP, the three public white papers, and lifecycle governance surfaces. This artifact does not claim vendor endorsement, official compatibility, legal compliance proof, insurance advice, coverage opinion, underwriting standard, insurer acceptance, coverage-ready status, underwriting-ready status, certification, regulator approval, external adoption, indexing, ranking, backlinks, answer-engine citation, external approval, or social announcement execution. The three white papers are available as public research editions with HTML, PDF, manifest, and checksum artifacts; AIIRWP v0.2 remains rejected and is not current source truth.",
  "nodes": [
    {
      "id": "jearon-wong",
      "name": "Jearon Wong",
      "type": "Person",
      "canonical_url": "https://www.jearonwong.com/about/",
      "source_authority": "owned-canonical",
      "description": "Protocol Architect for the Agent Era; creator of MPLP and author of the Global AI Compliance White Paper 2026, Agentic AI Auditability & Assurance White Paper 2026, and Agentic AI Insurability & Risk Transfer White Paper 2026.",
      "boundary": "Owned-canonical identity surface; no claim of regulator approval, vendor endorsement, external adoption, indexing, or answer-engine citation."
    },
    {
      "id": "mplp",
      "name": "MPLP",
      "type": "ProtocolProject",
      "canonical_url": "https://www.jearonwong.com/projects/mplp/",
      "source_authority": "project",
      "description": "One protocol path for lifecycle responsibility semantics in agentic and multi-agent work.",
      "boundary": "Not certification, legal compliance proof, required implementation, regulator-approved standard, vendor endorsement, or procurement guidance."
    },
    {
      "id": "mplp-v2-object-model-consolidation",
      "name": "MPLP v2.0 Object-Model Consolidation",
      "type": "ProtocolPhase",
      "canonical_url": "https://www.jearonwong.com/projects/mplp/",
      "source_authority": "project / held-next-phase",
      "description": "Next protocol work phase after the first three public research editions: consolidate the MPLP v2.0 protocol object model before the enterprise implementation white paper or practitioner guide public releases.",
      "boundary": "Next-phase positioning only; no fourth white paper, public guide, implementation mandate, certification, standard, regulator approval, or public announcement is claimed."
    },
    {
      "id": "gaic-white-paper-2026",
      "name": "Global AI Compliance White Paper 2026",
      "type": "TechnicalReport",
      "canonical_url": "https://www.jearonwong.com/research/global-ai-compliance-white-paper-2026/",
      "source_authority": "authored-analysis",
      "description": "Technical report GACWP-2026-v0.3.2-FRC-R3 defining Missing Regulatory Objects, RCCS-T, RCCS-M, ALCS, and lifecycle responsibility governance.",
      "boundary": "Not legal advice, legal compliance proof, certification, regulator-approved benchmark, vendor ranking, or procurement recommendation."
    },
    {
      "id": "agentic-lifecycle-governance",
      "name": "Agentic Lifecycle Governance",
      "type": "GovernanceConcept",
      "canonical_url": "https://www.jearonwong.com/concepts/agentic-lifecycle-governance/",
      "source_authority": "authored-analysis",
      "description": "Governance model for lifecycle responsibility in AI agent and multi-agent work.",
      "boundary": "Author-analytical concept; not regulator-approved guidance."
    },
    {
      "id": "missing-regulatory-objects",
      "name": "Missing Regulatory Objects",
      "type": "GovernanceObjectSet",
      "canonical_url": "https://www.jearonwong.com/concepts/missing-regulatory-objects/",
      "source_authority": "authored-analysis",
      "description": "Lifecycle responsibility objects that model-centric governance does not consistently define for agentic and multi-agent systems.",
      "boundary": "Analytical object layer; not current law or certification criteria."
    },
    {
      "id": "rccs-t",
      "name": "RCCS-T",
      "type": "EvaluationModel",
      "canonical_url": "https://www.jearonwong.com/research/global-ai-compliance-white-paper-2026/global-ai-compliance-white-paper-2026.html#rccs-t",
      "source_authority": "authored-analysis",
      "description": "Traditional Regulatory Compliance Coverage Score used in the GAIC white paper.",
      "boundary": "Analytical score language; not certification or procurement guidance."
    },
    {
      "id": "rccs-m",
      "name": "RCCS-M",
      "type": "EvaluationModel",
      "canonical_url": "https://www.jearonwong.com/concepts/rccs-m/",
      "source_authority": "authored-analysis",
      "description": "MRO-adjusted Regulatory Compliance Coverage Score.",
      "boundary": "Author-analytical adequacy model; not current law, certification, regulator approval, or procurement ranking."
    },
    {
      "id": "alcs",
      "name": "ALCS",
      "type": "EvaluationModel",
      "canonical_url": "https://www.jearonwong.com/concepts/alcs/",
      "source_authority": "authored-analysis",
      "description": "Agentic Lifecycle Conformance Score for lifecycle responsibility coherence.",
      "boundary": "Analytical conformance model; not certification or legal compliance proof."
    },
    {
      "id": "deterministic-delivery",
      "name": "Deterministic Delivery",
      "type": "EngineeringDiscipline",
      "canonical_url": "https://www.jearonwong.com/concepts/deterministic-delivery/",
      "source_authority": "authored-analysis",
      "description": "Discipline for making agentic work scoped, configured, authorized, evidenced, reviewable, accepted, remediable, and rollbackable.",
      "boundary": "Does not claim deterministic model outputs or guaranteed delivery."
    },
    {
      "id": "agentic-delivery",
      "name": "Agentic Delivery",
      "type": "CategoryConcept",
      "canonical_url": "https://www.jearonwong.com/concepts/agentic-delivery/",
      "source_authority": "authored-analysis",
      "description": "The missing layer between agent execution and accountable outcomes.",
      "boundary": "Category definition; not a closed standard or certification program."
    },
    {
      "id": "validation-lab",
      "name": "Validation Lab",
      "type": "Project",
      "canonical_url": "https://www.jearonwong.com/projects/validation-lab/",
      "source_authority": "project",
      "description": "MPLP evidence adjudication surface for evaluating evidence packs under versioned rulesets.",
      "boundary": "Non-certifying; not regulator approval, legal compliance proof, vendor endorsement, or procurement recommendation."
    },
    {
      "id": "cognitive-os",
      "name": "Cognitive OS",
      "type": "Project",
      "canonical_url": "https://www.jearonwong.com/projects/cognitive-os/",
      "source_authority": "project",
      "description": "Runtime path for protocol-native agent work.",
      "boundary": "Runtime path, not a completed universal runtime."
    },
    {
      "id": "solocrew",
      "name": "SoloCrew",
      "type": "Project",
      "canonical_url": "https://www.jearonwong.com/projects/solocrew/",
      "source_authority": "project",
      "description": "Delivery proof path for one-person-company AI operations.",
      "boundary": "Delivery proof path, not finished commercial proof or adoption evidence."
    },
    {
      "id": "systems-mapping",
      "name": "Systems Discussed in GAIC",
      "type": "SourceQualifiedMappingLayer",
      "canonical_url": "https://www.jearonwong.com/research/global-ai-compliance-white-paper-2026/systems/",
      "source_authority": "source-qualified mapping",
      "description": "Source-qualified, provisional, non-ranking lifecycle governance mappings for systems discussed in GAIC.",
      "boundary": "Not official vendor documentation, vendor ranking, procurement guidance, certification, or legal compliance proof."
    },
    {
      "id": "extended-ecosystem-mapping",
      "name": "Extended Ecosystem Mapping",
      "type": "SourceQualifiedMappingLayer",
      "canonical_url": "https://www.jearonwong.com/mapping/extended-ecosystem/",
      "source_authority": "source-qualified mapping",
      "description": "Source-qualified non-GAIC-scored mappings for adjacent ecosystem search contexts.",
      "boundary": "Not vendor ranking, official vendor documentation, vendor affiliation, certification, or procurement guidance."
    },
    {
      "id": "evidence-registry",
      "name": "Evidence Registry / Citation Kit",
      "type": "EvidenceRegistry",
      "canonical_url": "https://www.jearonwong.com/evidence/",
      "source_authority": "owned-canonical",
      "description": "Single citation and evidence shelf for Jearon Wong, MPLP, the three public white papers, and related source artifacts.",
      "boundary": "Evidence index; external evidence defaults to pending unless separately recorded."
    },
    {
      "id": "openai-agents-sdk",
      "name": "OpenAI Agents SDK",
      "type": "ExternalSystem",
      "canonical_url": "https://openai.github.io/openai-agents-python/",
      "source_authority": "external-official-source",
      "description": "External system treated as an interpretation subject in GAIC-related lifecycle governance mappings.",
      "boundary": "Official product facts remain with OpenAI official documentation."
    },
    {
      "id": "anthropic-claude-code",
      "name": "Claude Code",
      "type": "ExternalSystem",
      "canonical_url": "https://docs.anthropic.com/en/docs/claude-code/overview",
      "source_authority": "external-official-source",
      "description": "External system treated as an extended ecosystem interpretation subject.",
      "boundary": "Official product facts remain with Anthropic official documentation."
    },
    {
      "id": "langgraph",
      "name": "LangGraph",
      "type": "ExternalSystem",
      "canonical_url": "https://langchain-ai.github.io/langgraph/",
      "source_authority": "external-official-source",
      "description": "External framework treated as an interpretation subject in lifecycle governance mappings.",
      "boundary": "Official product facts remain with LangGraph / LangChain official documentation."
    },
    {
      "id": "a2a",
      "name": "Agent2Agent Protocol",
      "type": "ExternalProtocol",
      "canonical_url": "https://a2a-protocol.org/",
      "source_authority": "external-official-source",
      "description": "External protocol treated as an extended ecosystem interpretation subject.",
      "boundary": "Official protocol facts remain with official A2A documentation."
    },
    {
      "id": "mcp",
      "name": "Model Context Protocol",
      "type": "ExternalProtocol",
      "canonical_url": "https://modelcontextprotocol.io/",
      "source_authority": "external-official-source",
      "description": "External protocol treated as an extended ecosystem interpretation subject.",
      "boundary": "Official protocol facts remain with official MCP documentation."
    },
    {
      "id": "aws-bedrock-agentcore",
      "name": "AWS Bedrock / AgentCore",
      "type": "ExternalSystem",
      "canonical_url": "https://aws.amazon.com/bedrock/",
      "source_authority": "external-official-source",
      "description": "External system treated as an interpretation subject in GAIC lifecycle governance mapping.",
      "boundary": "Official product facts remain with AWS official documentation."
    },
    {
      "id": "ibm-watsonx-governance",
      "name": "IBM watsonx.governance",
      "type": "ExternalSystem",
      "canonical_url": "https://www.ibm.com/products/watsonx-governance",
      "source_authority": "external-official-source",
      "description": "External system treated as an interpretation subject in GAIC lifecycle governance mapping.",
      "boundary": "Official product facts remain with IBM official documentation."
    },
    {
      "id": "microsoft-ai-foundry",
      "name": "Microsoft Azure AI Foundry",
      "type": "ExternalSystem",
      "canonical_url": "https://learn.microsoft.com/en-us/azure/ai-foundry/",
      "source_authority": "external-official-source",
      "description": "External system treated as an interpretation subject in GAIC lifecycle governance mapping.",
      "boundary": "Official product facts remain with Microsoft official documentation."
    },
    {
      "id": "google-vertex-adk",
      "name": "Google Vertex AI / ADK",
      "type": "ExternalSystem",
      "canonical_url": "https://cloud.google.com/vertex-ai",
      "source_authority": "external-official-source",
      "description": "External system treated as an interpretation subject in GAIC lifecycle governance mapping.",
      "boundary": "Official product facts remain with Google official documentation."
    },
    {
      "id": "agentic-lifecycle-governance-industry-series",
      "name": "Agentic Lifecycle Governance Industry Series",
      "type": "CreativeWorkSeries",
      "canonical_url": "https://www.jearonwong.com/research/",
      "source_authority": "owned-canonical",
      "description": "White paper and guide series using the GAIC publication standard for lifecycle governance research assets. The first three white papers are available as official on-site public research editions; MPLP v2.0 object-model consolidation is the next protocol phase, and the enterprise implementation white paper plus practitioner guides are held until the protocol object model is ready.",
      "boundary": "Series grouping only; not certification, legal advice, regulator approval, external approval, or standards-body publication."
    },
    {
      "id": "aiaawp-white-paper-2026",
      "name": "Agentic AI Auditability & Assurance White Paper 2026",
      "type": "TechnicalReport",
      "canonical_url": "https://www.jearonwong.com/research/agentic-ai-auditability-assurance-white-paper-2026/",
      "source_authority": "authored-analysis",
      "description": "Public research edition for the Agentic AI Auditability & Assurance White Paper 2026, document ID AIAAWP-2026-v0.1, defining agentic AI auditability, audit evidence chains, AARM, and MRO-to-audit-evidence mapping.",
      "boundary": "Public research edition with production URL, artifact integrity, page-count, hash, homepage series, and sitewide semantic wiring aligned; not legal compliance proof, audit standard, certification, regulator approval, assurance opinion, endorsement, vendor ranking, or procurement guidance."
    },
    {
      "id": "agentic-ai-auditability",
      "name": "Agentic AI Auditability",
      "type": "GovernanceConcept",
      "canonical_url": "https://www.jearonwong.com/research/agentic-ai-auditability-assurance-white-paper-2026/agentic-ai-auditability-assurance-white-paper-2026.html#executive-thesis",
      "source_authority": "authored-analysis",
      "description": "Auditability framing for reconstructing agentic work through lifecycle evidence, authority, roles, tools, outcomes, exceptions, and closure.",
      "boundary": "Author-analytical concept; not an audit standard or assurance opinion."
    },
    {
      "id": "agentic-audit-object",
      "name": "Agentic Audit Object",
      "type": "GovernanceObject",
      "canonical_url": "https://www.jearonwong.com/research/agentic-ai-auditability-assurance-white-paper-2026/agentic-ai-auditability-assurance-white-paper-2026.html#agentic-audit-object-overview",
      "source_authority": "authored-analysis",
      "description": "Object model for lifecycle-linked auditability of agent work.",
      "boundary": "Proposed object model; not legal liability assignment or certification criteria."
    },
    {
      "id": "audit-evidence-chain",
      "name": "Audit Evidence Chain",
      "type": "GovernanceConcept",
      "canonical_url": "https://www.jearonwong.com/research/agentic-ai-auditability-assurance-white-paper-2026/agentic-ai-auditability-assurance-white-paper-2026.html#4-why-logs-are-not-audit-evidence-chains",
      "source_authority": "authored-analysis",
      "description": "Responsibility-linked evidence chain that distinguishes raw logs from reviewable audit evidence.",
      "boundary": "Evidence architecture concept; not an audit procedure or assurance conclusion."
    },
    {
      "id": "aarm",
      "name": "AARM",
      "type": "EvaluationModel",
      "canonical_url": "https://www.jearonwong.com/research/agentic-ai-auditability-assurance-white-paper-2026/agentic-ai-auditability-assurance-white-paper-2026.html#13-agentic-auditability-readiness-model",
      "source_authority": "authored-analysis",
      "description": "Agentic Auditability Readiness Model describing L0-L5 readiness levels and auditability dimensions.",
      "boundary": "Readiness model only; not certification, vendor score, assurance result, or legal compliance proof."
    },
    {
      "id": "mro-to-audit-evidence",
      "name": "MRO-to-Audit-Evidence Mapping",
      "type": "MappingLayer",
      "canonical_url": "https://www.jearonwong.com/research/agentic-ai-auditability-assurance-white-paper-2026/agentic-ai-auditability-assurance-white-paper-2026.html#6-mro-to-audit-evidence-mapping",
      "source_authority": "authored-analysis",
      "description": "Mapping from Global AI Compliance White Paper 2026 Missing Regulatory Objects to audit evidence objects in the Agentic AI Auditability & Assurance White Paper 2026.",
      "boundary": "Author-synthesis mapping; not regulator-approved mapping, audit standard, or procurement guidance."
    },
    {
      "id": "guide-1-audit-ready-ai-agent-systems",
      "name": "CIO/CTO Guide to Audit-Ready AI Agent Systems",
      "type": "PlannedGuide",
      "canonical_url": "https://www.jearonwong.com/research/agentic-ai-auditability-assurance-white-paper-2026/#series-title",
      "source_authority": "planned-series-reference",
      "description": "Held future practitioner guide that may translate the Agentic AI Auditability & Assurance White Paper 2026 into audit-ready technical implementation planning after MPLP v2.0 object-model consolidation is ready.",
      "boundary": "Held future asset; no public guide, implementation mandate, certification, or audit-standard claim is made."
    },
    {
      "id": "guide-2-agentic-lifecycle-governance",
      "name": "Chief Compliance Officer Guide to Agentic Lifecycle Governance",
      "type": "PlannedGuide",
      "canonical_url": "https://www.jearonwong.com/research/agentic-ai-auditability-assurance-white-paper-2026/#series-title",
      "source_authority": "planned-series-reference",
      "description": "Held future practitioner guide that may translate the Global AI Compliance White Paper 2026 and the Agentic AI Auditability & Assurance White Paper 2026 into compliance operating-model planning after MPLP v2.0 object-model consolidation is ready.",
      "boundary": "Held future asset; no public guide, legal advice, compliance proof, or regulator-approved method is claimed."
    },
    {
      "id": "aiirwp-white-paper-2026",
      "name": "Agentic AI Insurability & Risk Transfer White Paper 2026",
      "type": "TechnicalReport",
      "canonical_url": "https://www.jearonwong.com/research/agentic-ai-insurability-risk-transfer-white-paper-2026/",
      "source_authority": "authored-analysis / public-research-edition",
      "description": "Public research edition for the Agentic AI Insurability & Risk Transfer White Paper 2026, document ID AIIRWP-2026-v1.0, available with public HTML, PDF, manifest, and checksum artifacts. The withdrawn v0.2 public candidate remains rejected and is not current source truth or citation source.",
      "boundary": "Public research edition available; not legal advice, not insurance advice, not coverage opinion, not underwriting standard, not underwriting guidance, not certification, not proof of insurability, not insurer acceptance, not coverage-ready, not underwriting-ready, not claim-ready, not score, not standard, and not regulator approval.",
      "artifacts": {
        "html": "https://www.jearonwong.com/research/agentic-ai-insurability-risk-transfer-white-paper-2026/agentic-ai-insurability-risk-transfer-white-paper-2026.html",
        "pdf": "https://www.jearonwong.com/research/agentic-ai-insurability-risk-transfer-white-paper-2026/agentic-ai-insurability-risk-transfer-white-paper-2026.pdf",
        "manifest": "https://www.jearonwong.com/research/agentic-ai-insurability-risk-transfer-white-paper-2026/manifest.json",
        "checksums": "https://www.jearonwong.com/research/agentic-ai-insurability-risk-transfer-white-paper-2026/checksums.sha256"
      }
    },
    {
      "id": "agentic-ai-insurability",
      "name": "Agentic AI Insurability",
      "type": "GovernanceConcept",
      "canonical_url": "https://www.jearonwong.com/research/agentic-ai-insurability-risk-transfer-white-paper-2026/",
      "source_authority": "author-synthesis / public-research-edition",
      "description": "The Agentic AI Insurability & Risk Transfer White Paper 2026 v1.0 public research edition frames agentic work through lifecycle evidence, responsibility mapping, bounded risk objects, and claim-reviewable records.",
      "boundary": "Author-analytical concept; not insurance advice, coverage opinion, insurer acceptance, coverage-ready status, underwriting-ready status, claim-ready status, or underwriting standard. Withdrawn v0.2 is not current source truth."
    },
    {
      "id": "agentic-insurability-objects",
      "name": "Agentic Insurability Objects",
      "type": "GovernanceObject",
      "canonical_url": "https://www.jearonwong.com/research/agentic-ai-insurability-risk-transfer-white-paper-2026/",
      "source_authority": "author-synthesis / public-research-edition",
      "description": "AIO is a Jearon Wong analytical object model for separating insured legal subject, agentic risk object, authority, responsibility, evidence, loss reconstruction, dependency, aggregation, and dispute-readiness questions.",
      "boundary": "Author-synthesis object model; not an insurer product requirement, policy term, legal liability object, proof of insurability, or certification criterion. Withdrawn v0.2 is not current source truth."
    },
    {
      "id": "insured-legal-subject",
      "name": "Insured Legal Subject",
      "type": "GovernanceConcept",
      "canonical_url": "https://www.jearonwong.com/research/agentic-ai-insurability-risk-transfer-white-paper-2026/",
      "source_authority": "author-synthesis / public-research-edition",
      "description": "The Agentic AI Insurability & Risk Transfer White Paper 2026 v1.0 public research edition uses this concept for the person or organization whose risk-transfer relationship must remain separate from the agentic system, work unit, tool, model, or workflow being analyzed.",
      "boundary": "Not a liability determination, coverage opinion, insured-status opinion, or conclusion that a policy applies. Current v0.2 artifact is withdrawn and not current source truth."
    },
    {
      "id": "agentic-risk-object",
      "name": "Agentic Risk Object",
      "type": "GovernanceObject",
      "canonical_url": "https://www.jearonwong.com/research/agentic-ai-insurability-risk-transfer-white-paper-2026/",
      "source_authority": "author-synthesis / public-research-edition",
      "description": "The Agentic AI Insurability & Risk Transfer White Paper 2026 v1.0 public research edition uses this concept for the bounded agentic work unit, action path, dependency, evidence chain, or loss-relevant lifecycle object being evaluated for risk-transfer analysis.",
      "boundary": "Not the insured party, not a legal subject, not a standalone coverage trigger, and not a claim that a system is insurable. Current v0.2 artifact is withdrawn and not current source truth."
    },
    {
      "id": "claim-evidence-chain",
      "name": "Claim Evidence Chain",
      "type": "GovernanceConcept",
      "canonical_url": "https://www.jearonwong.com/research/agentic-ai-insurability-risk-transfer-white-paper-2026/",
      "source_authority": "author-synthesis / public-research-edition",
      "description": "The Agentic AI Insurability & Risk Transfer White Paper 2026 v1.0 public research edition uses this concept for lifecycle evidence needed to reconstruct authority, action, loss event, dependency, remediation, dispute posture, and boundary risk for claim review.",
      "boundary": "Not claims approval guidance, a payment guarantee, legal causation proof, settlement advice, coverage opinion, or an insurer-required form. Withdrawn v0.2 is not current source truth."
    },
    {
      "id": "airm",
      "name": "AIRM",
      "type": "EvaluationModel",
      "canonical_url": "https://www.jearonwong.com/research/agentic-ai-insurability-risk-transfer-white-paper-2026/",
      "source_authority": "author-synthesis / public-research-edition",
      "description": "AIRM is a Jearon Wong authored non-scoring reasoning model for evidence visibility and risk-transfer reasoning vocabulary.",
      "boundary": "Non-scoring reasoning vocabulary only; not actuarial pricing guidance, certification, insurer acceptance, coverage guarantee, underwriting standard, claims approval guidance, vendor score, readiness certification, or procurement benchmark. Withdrawn v0.2 is not current source truth."
    }
  ],
  "edges": [
    {
      "source": "jearon-wong",
      "relation": "created",
      "target": "mplp",
      "evidence_status": "owned-canonical",
      "evidence_url": "https://www.jearonwong.com/projects/mplp/",
      "boundary": "Creator relation is self-owned/project-owned; no external adoption claim."
    },
    {
      "source": "jearon-wong",
      "relation": "authored",
      "target": "gaic-white-paper-2026",
      "evidence_status": "authored-analysis",
      "evidence_url": "https://www.jearonwong.com/research/global-ai-compliance-white-paper-2026/",
      "boundary": "Authorship relation; no claim that external systems cite or adopt it."
    },
    {
      "source": "jearon-wong",
      "relation": "defines",
      "target": "agentic-lifecycle-governance",
      "evidence_status": "authored-analysis",
      "evidence_url": "https://www.jearonwong.com/concepts/agentic-lifecycle-governance/",
      "boundary": "Concept definition, not official regulator guidance."
    },
    {
      "source": "jearon-wong",
      "relation": "defines",
      "target": "missing-regulatory-objects",
      "evidence_status": "authored-analysis",
      "evidence_url": "https://www.jearonwong.com/concepts/missing-regulatory-objects/",
      "boundary": "Analytical object layer, not current law."
    },
    {
      "source": "jearon-wong",
      "relation": "defines",
      "target": "rccs-m",
      "evidence_status": "authored-analysis",
      "evidence_url": "https://www.jearonwong.com/concepts/rccs-m/",
      "boundary": "Analytical score model, not certification."
    },
    {
      "source": "jearon-wong",
      "relation": "defines",
      "target": "alcs",
      "evidence_status": "authored-analysis",
      "evidence_url": "https://www.jearonwong.com/concepts/alcs/",
      "boundary": "Analytical conformance model, not legal compliance proof."
    },
    {
      "source": "jearon-wong",
      "relation": "defines",
      "target": "deterministic-delivery",
      "evidence_status": "authored-analysis",
      "evidence_url": "https://www.jearonwong.com/concepts/deterministic-delivery/",
      "boundary": "Engineering discipline, not deterministic LLM output claim."
    },
    {
      "source": "mplp",
      "relation": "is_one_protocol_path_for",
      "target": "agentic-lifecycle-governance",
      "evidence_status": "project",
      "evidence_url": "https://www.jearonwong.com/projects/mplp/",
      "boundary": "One protocol path only; not required, exclusive, certified, or regulator-approved."
    },
    {
      "source": "agentic-lifecycle-governance-industry-series",
      "relation": "has_next_protocol_phase",
      "target": "mplp-v2-object-model-consolidation",
      "evidence_status": "held-next-phase",
      "evidence_url": "https://www.jearonwong.com/research/",
      "boundary": "Positioning relation only; the enterprise implementation white paper and practitioner guides remain held and are not publicly released."
    },
    {
      "source": "gaic-white-paper-2026",
      "relation": "introduces",
      "target": "missing-regulatory-objects",
      "evidence_status": "authored-analysis",
      "evidence_url": "https://www.jearonwong.com/research/global-ai-compliance-white-paper-2026/",
      "boundary": "Author-analytical introduction; not law or certification."
    },
    {
      "source": "gaic-white-paper-2026",
      "relation": "introduces",
      "target": "rccs-t",
      "evidence_status": "authored-analysis",
      "evidence_url": "https://www.jearonwong.com/research/global-ai-compliance-white-paper-2026/global-ai-compliance-white-paper-2026.html#rccs-t",
      "boundary": "Analytical score language; not vendor ranking."
    },
    {
      "source": "gaic-white-paper-2026",
      "relation": "introduces",
      "target": "rccs-m",
      "evidence_status": "authored-analysis",
      "evidence_url": "https://www.jearonwong.com/concepts/rccs-m/",
      "boundary": "Analytical score language; not certification."
    },
    {
      "source": "gaic-white-paper-2026",
      "relation": "introduces",
      "target": "alcs",
      "evidence_status": "authored-analysis",
      "evidence_url": "https://www.jearonwong.com/concepts/alcs/",
      "boundary": "Analytical conformance language; not legal compliance proof."
    },
    {
      "source": "missing-regulatory-objects",
      "relation": "maps_to",
      "target": "agentic-lifecycle-governance",
      "evidence_status": "authored-analysis",
      "evidence_url": "https://www.jearonwong.com/concepts/agentic-lifecycle-governance/",
      "boundary": "Maps regulatory language into lifecycle responsibility objects as author analysis."
    },
    {
      "source": "rccs-m",
      "relation": "supports",
      "target": "gaic-white-paper-2026",
      "evidence_status": "authored-analysis",
      "evidence_url": "https://www.jearonwong.com/research/global-ai-compliance-white-paper-2026/",
      "boundary": "Supports GAIC analytical framework only."
    },
    {
      "source": "alcs",
      "relation": "supports",
      "target": "gaic-white-paper-2026",
      "evidence_status": "authored-analysis",
      "evidence_url": "https://www.jearonwong.com/research/global-ai-compliance-white-paper-2026/",
      "boundary": "Supports GAIC analytical framework only."
    },
    {
      "source": "validation-lab",
      "relation": "is_evidence_surface_for",
      "target": "mplp",
      "evidence_status": "project",
      "evidence_url": "https://www.jearonwong.com/projects/validation-lab/",
      "boundary": "Evidence surface, not certification body."
    },
    {
      "source": "cognitive-os",
      "relation": "is_runtime_path_for",
      "target": "agentic-delivery",
      "evidence_status": "project",
      "evidence_url": "https://www.jearonwong.com/projects/cognitive-os/",
      "boundary": "Runtime path, not universal runtime claim."
    },
    {
      "source": "solocrew",
      "relation": "is_product_proof_path_for",
      "target": "agentic-delivery",
      "evidence_status": "project",
      "evidence_url": "https://www.jearonwong.com/projects/solocrew/",
      "boundary": "Delivery proof path, not external adoption evidence."
    },
    {
      "source": "systems-mapping",
      "relation": "interprets_under_lifecycle_governance",
      "target": "openai-agents-sdk",
      "evidence_status": "source-qualified mapping",
      "evidence_url": "https://www.jearonwong.com/research/global-ai-compliance-white-paper-2026/systems/",
      "boundary": "Interpretation subject only; official product facts remain with OpenAI."
    },
    {
      "source": "extended-ecosystem-mapping",
      "relation": "interprets_under_lifecycle_governance",
      "target": "anthropic-claude-code",
      "evidence_status": "source-qualified mapping",
      "evidence_url": "https://www.jearonwong.com/mapping/extended-ecosystem/claude-code/",
      "boundary": "Interpretation subject only; official product facts remain with Anthropic."
    },
    {
      "source": "systems-mapping",
      "relation": "interprets_under_lifecycle_governance",
      "target": "langgraph",
      "evidence_status": "source-qualified mapping",
      "evidence_url": "https://www.jearonwong.com/research/global-ai-compliance-white-paper-2026/systems/",
      "boundary": "Interpretation subject only; official product facts remain with LangGraph / LangChain."
    },
    {
      "source": "extended-ecosystem-mapping",
      "relation": "interprets_under_lifecycle_governance",
      "target": "a2a",
      "evidence_status": "source-qualified mapping",
      "evidence_url": "https://www.jearonwong.com/mapping/extended-ecosystem/a2a/",
      "boundary": "Interpretation subject only; official protocol facts remain with official A2A documentation."
    },
    {
      "source": "extended-ecosystem-mapping",
      "relation": "interprets_under_lifecycle_governance",
      "target": "mcp",
      "evidence_status": "source-qualified mapping",
      "evidence_url": "https://www.jearonwong.com/mapping/extended-ecosystem/mcp/",
      "boundary": "Interpretation subject only; official protocol facts remain with official MCP documentation."
    },
    {
      "source": "systems-mapping",
      "relation": "interprets_under_lifecycle_governance",
      "target": "aws-bedrock-agentcore",
      "evidence_status": "source-qualified mapping",
      "evidence_url": "https://www.jearonwong.com/research/global-ai-compliance-white-paper-2026/systems/",
      "boundary": "Interpretation subject only; official product facts remain with AWS."
    },
    {
      "source": "systems-mapping",
      "relation": "interprets_under_lifecycle_governance",
      "target": "ibm-watsonx-governance",
      "evidence_status": "source-qualified mapping",
      "evidence_url": "https://www.jearonwong.com/research/global-ai-compliance-white-paper-2026/systems/",
      "boundary": "Interpretation subject only; official product facts remain with IBM."
    },
    {
      "source": "systems-mapping",
      "relation": "interprets_under_lifecycle_governance",
      "target": "microsoft-ai-foundry",
      "evidence_status": "source-qualified mapping",
      "evidence_url": "https://www.jearonwong.com/research/global-ai-compliance-white-paper-2026/systems/",
      "boundary": "Interpretation subject only; official product facts remain with Microsoft."
    },
    {
      "source": "systems-mapping",
      "relation": "interprets_under_lifecycle_governance",
      "target": "google-vertex-adk",
      "evidence_status": "source-qualified mapping",
      "evidence_url": "https://www.jearonwong.com/research/global-ai-compliance-white-paper-2026/systems/",
      "boundary": "Interpretation subject only; official product facts remain with Google."
    },
    {
      "source": "evidence-registry",
      "relation": "is_evidence_surface_for",
      "target": "jearon-wong",
      "evidence_status": "owned-canonical",
      "evidence_url": "https://www.jearonwong.com/evidence/",
      "boundary": "Citation and evidence index only; external evidence remains pending unless separately recorded."
    },
    {
      "source": "evidence-registry",
      "relation": "is_evidence_surface_for",
      "target": "mplp",
      "evidence_status": "owned-canonical",
      "evidence_url": "https://www.jearonwong.com/evidence/",
      "boundary": "Citation and evidence index only; no adoption or official compatibility claim."
    },
    {
      "source": "evidence-registry",
      "relation": "is_evidence_surface_for",
      "target": "gaic-white-paper-2026",
      "evidence_status": "owned-canonical",
      "evidence_url": "https://www.jearonwong.com/evidence/",
      "boundary": "Citation and evidence index only; no answer-engine or indexing outcome claim."
    },
    {
      "source": "jearon-wong",
      "relation": "authored",
      "target": "aiaawp-white-paper-2026",
      "evidence_status": "authored-analysis",
      "evidence_url": "https://www.jearonwong.com/research/agentic-ai-auditability-assurance-white-paper-2026/",
      "boundary": "Authorship relation for public research edition; no external adoption, indexing, certification, or assurance claim."
    },
    {
      "source": "aiaawp-white-paper-2026",
      "relation": "belongs_to",
      "target": "agentic-lifecycle-governance-industry-series",
      "evidence_status": "owned-canonical",
      "evidence_url": "https://www.jearonwong.com/research/agentic-ai-auditability-assurance-white-paper-2026/",
      "boundary": "Series relationship only; not an external approval claim."
    },
    {
      "source": "aiaawp-white-paper-2026",
      "relation": "builds_on",
      "target": "gaic-white-paper-2026",
      "evidence_status": "authored-analysis",
      "evidence_url": "https://www.jearonwong.com/research/agentic-ai-auditability-assurance-white-paper-2026/",
      "boundary": "Companion-paper relationship; GAIC artifacts and methodology remain unchanged."
    },
    {
      "source": "aiaawp-white-paper-2026",
      "relation": "defines",
      "target": "agentic-ai-auditability",
      "evidence_status": "authored-analysis",
      "evidence_url": "https://www.jearonwong.com/research/agentic-ai-auditability-assurance-white-paper-2026/",
      "boundary": "Concept definition, not an audit standard."
    },
    {
      "source": "aiaawp-white-paper-2026",
      "relation": "defines",
      "target": "agentic-audit-object",
      "evidence_status": "authored-analysis",
      "evidence_url": "https://www.jearonwong.com/research/agentic-ai-auditability-assurance-white-paper-2026/",
      "boundary": "Object-model definition, not legal liability assignment."
    },
    {
      "source": "aiaawp-white-paper-2026",
      "relation": "formalizes",
      "target": "aarm",
      "evidence_status": "authored-analysis",
      "evidence_url": "https://www.jearonwong.com/research/agentic-ai-auditability-assurance-white-paper-2026/",
      "boundary": "Readiness model only; no certification or assurance result."
    },
    {
      "source": "aiaawp-white-paper-2026",
      "relation": "formalizes",
      "target": "audit-evidence-chain",
      "evidence_status": "authored-analysis",
      "evidence_url": "https://www.jearonwong.com/research/agentic-ai-auditability-assurance-white-paper-2026/",
      "boundary": "Evidence-chain formalization only; not an audit procedure or assurance opinion."
    },
    {
      "source": "aiaawp-white-paper-2026",
      "relation": "maps_to",
      "target": "mro-to-audit-evidence",
      "evidence_status": "authored-analysis",
      "evidence_url": "https://www.jearonwong.com/research/agentic-ai-auditability-assurance-white-paper-2026/",
      "boundary": "Mapping layer, not regulator-approved guidance."
    },
    {
      "source": "mro-to-audit-evidence",
      "relation": "builds_on",
      "target": "missing-regulatory-objects",
      "evidence_status": "authored-analysis",
      "evidence_url": "https://www.jearonwong.com/research/agentic-ai-auditability-assurance-white-paper-2026/",
      "boundary": "Derived from GAIC source truth without changing GAIC scores or methodology."
    },
    {
      "source": "aiaawp-white-paper-2026",
      "relation": "supports",
      "target": "guide-1-audit-ready-ai-agent-systems",
      "evidence_status": "planned-series-reference",
      "evidence_url": "https://www.jearonwong.com/research/agentic-ai-auditability-assurance-white-paper-2026/",
      "boundary": "Support relation for future planning only; no public guide artifact is claimed."
    },
    {
      "source": "aiaawp-white-paper-2026",
      "relation": "supports",
      "target": "guide-2-agentic-lifecycle-governance",
      "evidence_status": "planned-series-reference",
      "evidence_url": "https://www.jearonwong.com/research/agentic-ai-auditability-assurance-white-paper-2026/",
      "boundary": "Support relation for future planning only; no legal or compliance result is claimed."
    },
    {
      "source": "aiaawp-white-paper-2026",
      "relation": "complements",
      "target": "aiirwp-white-paper-2026",
      "evidence_status": "authored-analysis",
      "evidence_url": "https://www.jearonwong.com/research/agentic-ai-insurability-risk-transfer-white-paper-2026/",
      "boundary": "Sibling research relationship only; auditability supports insurability analysis but does not equal insurance advice, coverage opinion, insurer acceptance, or underwriting standard."
    },
    {
      "source": "evidence-registry",
      "relation": "is_evidence_surface_for",
      "target": "aiaawp-white-paper-2026",
      "evidence_status": "owned-canonical",
      "evidence_url": "https://www.jearonwong.com/evidence/",
      "boundary": "Citation and evidence index only; no answer-engine or indexing outcome claim."
    },
    {
      "source": "jearon-wong",
      "relation": "authored",
      "target": "aiirwp-white-paper-2026",
      "evidence_status": "public-research-edition",
      "evidence_url": "https://www.jearonwong.com/research/agentic-ai-insurability-risk-transfer-white-paper-2026/",
      "boundary": "Authorship relation for the Agentic AI Insurability & Risk Transfer White Paper 2026 v1.0 public research edition; no external adoption, indexing, certification, insurer acceptance, coverage-ready status, underwriting-ready status, claim-ready status, or public announcement claim."
    },
    {
      "source": "aiirwp-white-paper-2026",
      "relation": "belongs_to",
      "target": "agentic-lifecycle-governance-industry-series",
      "evidence_status": "public-research-edition",
      "evidence_url": "https://www.jearonwong.com/research/agentic-ai-insurability-risk-transfer-white-paper-2026/",
      "boundary": "Series relationship only; the Agentic AI Insurability & Risk Transfer White Paper 2026 v1.0 is available as a public research edition and v0.2 remains rejected."
    },
    {
      "source": "aiirwp-white-paper-2026",
      "relation": "interprets",
      "target": "gaic-white-paper-2026",
      "evidence_status": "public-research-edition",
      "evidence_url": "https://www.jearonwong.com/research/agentic-ai-insurability-risk-transfer-white-paper-2026/",
      "boundary": "Insurability and risk-transfer interpretation of the root lifecycle governance framework; no claim that GAIC makes systems insurable."
    },
    {
      "source": "aiirwp-white-paper-2026",
      "relation": "defines",
      "target": "agentic-ai-insurability",
      "evidence_status": "public-research-edition",
      "evidence_url": "https://www.jearonwong.com/research/agentic-ai-insurability-risk-transfer-white-paper-2026/",
      "boundary": "Concept definition, not insurance advice or coverage opinion."
    },
    {
      "source": "aiirwp-white-paper-2026",
      "relation": "defines",
      "target": "agentic-insurability-objects",
      "evidence_status": "public-research-edition",
      "evidence_url": "https://www.jearonwong.com/research/agentic-ai-insurability-risk-transfer-white-paper-2026/",
      "boundary": "Object-model definition, not insurer product requirement or certification criterion."
    },
    {
      "source": "agentic-insurability-objects",
      "relation": "separates",
      "target": "insured-legal-subject",
      "evidence_status": "public-research-edition",
      "evidence_url": "https://www.jearonwong.com/research/agentic-ai-insurability-risk-transfer-white-paper-2026/",
      "boundary": "Analytical separation only; not legal liability determination."
    },
    {
      "source": "agentic-insurability-objects",
      "relation": "separates",
      "target": "agentic-risk-object",
      "evidence_status": "public-research-edition",
      "evidence_url": "https://www.jearonwong.com/research/agentic-ai-insurability-risk-transfer-white-paper-2026/",
      "boundary": "Analytical separation only; not coverage trigger or insurability guarantee."
    },
    {
      "source": "aiirwp-white-paper-2026",
      "relation": "formalizes",
      "target": "claim-evidence-chain",
      "evidence_status": "public-research-edition",
      "evidence_url": "https://www.jearonwong.com/research/agentic-ai-insurability-risk-transfer-white-paper-2026/",
      "boundary": "Evidence-chain formalization only; not claims approval guidance or payment guarantee."
    },
    {
      "source": "aiirwp-white-paper-2026",
      "relation": "formalizes",
      "target": "airm",
      "evidence_status": "public-research-edition",
      "evidence_url": "https://www.jearonwong.com/research/agentic-ai-insurability-risk-transfer-white-paper-2026/",
      "boundary": "Readiness model only; no actuarial score, certification, insurer acceptance, coverage guarantee, underwriting standard, or claims approval guidance."
    },
    {
      "source": "evidence-registry",
      "relation": "is_evidence_surface_for",
      "target": "aiirwp-white-paper-2026",
      "evidence_status": "owned-canonical",
      "evidence_url": "https://www.jearonwong.com/evidence/",
      "boundary": "Citation and evidence index only; no answer-engine, indexing, insurer acceptance, coverage-ready, underwriting-ready, claim-ready, certification, external approval, or production-verification outcome claim."
    }
  ]
}
