{
  "schemaVersion": "pal-architecture-evolution-v1",
  "nodes": [
    {
      "id": "ai-vs-sap-observations",
      "label": "AI vs SAP field observations",
      "date": "2026-06-14",
      "stage": "Observation",
      "publicationId": "eight-honest-observations-ai-real-sap-work",
      "problem": "Generic AI can sound useful while missing SAP-specific evidence and operating context.",
      "experiment": "Compare AI outputs against practical SAP architecture and diagnostic scenarios.",
      "architecture": "Separate generated explanation from SAP evidence and expert accountability.",
      "evidence": "Public LinkedIn observation series.",
      "learning": "Evidence and context must be visible before AI advice is promoted.",
      "maturity": "PUBLISHED",
      "nextQuestion": "How should an agent consume SAP evidence safely?"
    },
    {
      "id": "adt-mcp-cds-experiment",
      "label": "Cline, Eclipse ADT and SAP ADT MCP",
      "date": "2026-07-18",
      "stage": "Experiment",
      "publicationId": "active-sap-cds-view-cline-eclipse-adt-mcp",
      "productId": "abap4c-cloud-deployment-pipeline-architecture-1",
      "problem": "AI-assisted SAP development needs a controlled route from requirement to target-system evidence.",
      "experiment": "Connect Cline, Eclipse ADT and SAP ADT MCP around CDS-view creation and activation.",
      "architecture": "Standards-led ADT MCP path with proof boundaries.",
      "evidence": "Public LinkedIn article and bounded architecture record.",
      "learning": "Protocol success, activation proof and semantic correctness must be separated.",
      "maturity": "PUBLIC_SAFE_EVIDENCE",
      "nextQuestion": "Can this become a repeatable ABAP Cloud architecture option?"
    },
    {
      "id": "abap4c-architecture-option-1",
      "label": "ABAP4C Architecture Option 1",
      "date": "2026-07-26",
      "stage": "Architecture",
      "publicationId": "abap4c-architecture-option-1",
      "productId": "abap4c-cloud-deployment-pipeline-architecture-1",
      "problem": "ABAP Cloud automation needs an explainable architecture option with SAP execution controls.",
      "experiment": "Model the direct AI or coding-agent to ADT MCP route.",
      "architecture": "AI/Coding Agent to VS Code/Cline/Python to Standard ADT MCP to SAP ADT tools.",
      "evidence": "Public article plus product architecture record.",
      "learning": "A direct standards path is useful when scope, provider schema and proof limits remain visible.",
      "maturity": "PUBLISHED",
      "nextQuestion": "Where does a governed bridge add control?"
    },
    {
      "id": "abap4clayer-lessons",
      "label": "ABAP4CLayer hands-on lessons",
      "date": "2026-08-06",
      "stage": "Validation",
      "publicationId": "abap4clayer-architecture-option-1-25-lessons",
      "productId": "abap4c-cloud-deployment-pipeline-capella",
      "problem": "Generated SAP code is not validated SAP capability until execution, receipts and boundaries are proven.",
      "experiment": "Use an ABAP4CLayer architecture to test AI-assisted SAP code generation and automation controls.",
      "architecture": "Governed bridge pattern with explicit execution and validation gates.",
      "evidence": "Public LinkedIn lessons; public website describes only sanitized architecture boundaries.",
      "learning": "Generated, activated and runtime-proven states must not be collapsed into one claim.",
      "maturity": "PUBLIC_SAFE_EVIDENCE",
      "nextQuestion": "How does the SAP architect role evolve around these controls?"
    },
    {
      "id": "sap-architect-ai-engineering",
      "label": "SAP architect to AI engineering",
      "date": "2026-08-10",
      "stage": "Learning",
      "publicationId": "sap-development-architect-automation-to-ai-engineering",
      "productId": "capai-engineering-control-center",
      "problem": "SAP automation work needs a broader AI engineering discipline, not just faster tooling.",
      "experiment": "Synthesize architecture, validation, governance and human-control lessons into a role model.",
      "architecture": "Evidence-aware AI engineering with deterministic authority and human production gates.",
      "evidence": "Public LinkedIn article and website governance model.",
      "learning": "The architecture role expands toward evidence systems, controls, release reliability and accountable AI.",
      "maturity": "PUBLISHED",
      "nextQuestion": "Which public research question should be validated next?"
    }
  ],
  "relationships": [
    {
      "from": "adt-mcp-cds-experiment",
      "to": "ai-vs-sap-observations",
      "type": "informed_by"
    },
    {
      "from": "abap4c-architecture-option-1",
      "to": "adt-mcp-cds-experiment",
      "type": "evolved_from"
    },
    {
      "from": "abap4clayer-lessons",
      "to": "abap4c-architecture-option-1",
      "type": "compared_with"
    },
    {
      "from": "sap-architect-ai-engineering",
      "to": "abap4clayer-lessons",
      "type": "informed_by"
    }
  ]
}