{
  "version": "4.12.0",
  "generatedUtc": "2026-08-17T23:59:00Z",
  "sourceStatus": "approved",
  "primaryTitle": "Machine Intelligence Engineer / Software Architect",
  "secondaryDescriptor": "Senior Software Architect | AI Systems, Multi-Agent Coordination & LLM Infrastructure",
  "corePositioning": "Michael Kappel architects machine-intelligence systems for multi-agent coordination, persistent AI memory, local LLM infrastructure, governed workflows, and enterprise AI integration, backed by more than two decades of .NET, Azure, SQL, TypeScript, testing, and production software engineering.",
  "pillars": [
    {
      "id": "multi-agent-systems",
      "name": "Multi-Agent Systems",
      "summary": "Coordination infrastructure for external AI agents through registered identity, governed scope, durable context, rooms, messages, acknowledgements, and conflict-aware work ownership.",
      "route": "/multi-agent-systems/",
      "primaryEvidence": "https://github.com/MichaelKappel/Multi-Agent-Memory"
    },
    {
      "id": "persistent-ai-memory",
      "name": "Persistent AI Memory",
      "summary": "Typed local .uai startup and recovery continuity augmented by authenticated, scoped, reviewed shared memory and human verification.",
      "route": "/ai-memory/",
      "primaryEvidence": "https://uaix.org/en-us/tools/ai-memory-package-wizard/"
    },
    {
      "id": "llm-infrastructure",
      "name": "LLM Infrastructure",
      "summary": "Public .NET components for local model runtime contracts, GGUF/LLaMA-oriented execution, tensors, tokenization, sampling, backends, browser/P2P tooling, interoperability, governance, and observability.",
      "route": "/llm-infrastructure/",
      "primaryEvidence": "https://www.nuget.org/profiles/Michael.Kappel"
    },
    {
      "id": "enterprise-ai-integration",
      "name": "Enterprise AI Integration",
      "summary": "Model APIs, retrieval, structured output, validation, recovery, observability, and human review integrated with long-lived business software.",
      "route": "/machine-intelligence/",
      "primaryEvidence": "/experience/"
    },
    {
      "id": "enterprise-engineering-foundation",
      "name": "Enterprise Engineering Foundation",
      "summary": "20+ years across Microsoft Azure, .NET, SQL Server, TypeScript/Angular, testing, modernization, delivery, and mentoring.",
      "route": "/experience/",
      "primaryEvidence": "/resume/"
    },
    {
      "id": "applied-ai-modernization",
      "name": "Applied AI Modernization",
      "summary": "Process-first AI integration for existing enterprise software: code intelligence, AI API documentation, governed knowledge/retrieval, legal/intake workflow patterns, recovery, and bounded automation.",
      "route": "/machine-intelligence/",
      "primaryEvidence": "https://intelligence724.com/"
    }
  ],
  "proofMetrics": {
    "enterpriseEngineeringYears": "20+",
    "azureContinuity": "Every professional role since 2010; user-confirmed role-level services and usage contexts",
    "publicNuGetPackages": 32,
    "cumulativeNuGetDownloads": "21K+",
    "multiAgentMemoryEdition": "Public source-available reference implementation 0.2.0"
  },
  "selectedEvidence": [
    {
      "name": "Multi-Agent Memory",
      "type": "SoftwareSourceCode",
      "classification": "publicly verified",
      "summary": "Deployable private-intranet multi-agent coordination and memory reference implementation for external agents.",
      "url": "https://github.com/MichaelKappel/Multi-Agent-Memory",
      "companion": "https://multiagentmemory.com/"
    },
    {
      "name": "Intelligence724",
      "type": "Professional capability surface",
      "classification": "live-verified capability-level evidence",
      "summary": "Applied machine intelligence for existing enterprise systems: AI-enabled workflows, code intelligence and documentation, legacy modernization, governed knowledge/memory systems, and bounded automation.",
      "url": "https://intelligence724.com/",
      "companion": "https://intelligence724.com/ai-delivery-experience/",
      "claimBoundary": "Intelligence724 and Info724 share consulting heritage, but do not claim they are identical companies or that every historic Info724 engagement is an Intelligence724 engagement. Do not expose confidential client identities, exact private systems, proprietary workflow details, source code, production data, credentials, lead volumes, financial metrics, conversion metrics, or unsupported outcomes. Re-check current Intelligence724 public pages before making current factual claims."
    },
    {
      "name": "UAIX / UAI-1 / .uai continuity",
      "type": "Technical standard and tooling",
      "classification": "publicly verified",
      "summary": "Typed local-first identity, constraints, context, progress, handoff, recovery, and reviewed communication records.",
      "url": "https://uaix.org/en-us/tools/ai-memory-package-wizard/"
    },
    {
      "name": "Michael.Kappel NuGet ecosystem",
      "type": "Package registry evidence",
      "classification": "publicly verified",
      "summary": "32 public .NET packages with 21K+ cumulative downloads, including a 17-package local LLM runtime family.",
      "url": "https://www.nuget.org/profiles/Michael.Kappel"
    },
    {
      "name": "Confidential lead/intake workflow",
      "type": "User-supplied professional evidence",
      "classification": "user-confirmed; confidential",
      "summary": "Coordinated AI workflow patterns separating specialized responsibilities, shared context, validation, recovery, and human escalation.",
      "url": "/experience/"
    }
  ],
  "targetRoles": {
    "primary": [
      "AI Systems Architect",
      "Machine Intelligence Engineer",
      "Multi-Agent Systems Engineer",
      "AI Developer Tools / LLM Infrastructure Engineer",
      "Enterprise AI Architect"
    ],
    "supportedWithContext": [
      "Senior AI Software Engineer",
      "AI Platform Engineer",
      "Applied AI Engineer",
      "Senior Software Architect"
    ],
    "avoidWithoutAdditionalEvidence": [
      "Machine Learning Researcher",
      "Data Scientist",
      "Foundation Model Researcher",
      "Model Training Scientist"
    ]
  },
  "reviewOrder": [
    "/",
    "/machine-intelligence/",
    "/multi-agent-systems/",
    "/ai-memory/",
    "/llm-infrastructure/",
    "https://intelligence724.com/",
    "/projects/",
    "/resume/",
    "/experience/",
    "/case-studies/multi-agent-memory/"
  ],
  "claimBoundaries": [
    "Intelligence724 is capability-level public evidence for applied AI modernization; it does not disclose confidential Info724/client systems or prove every historic Info724 engagement was an Intelligence724 engagement.",
    "Multi-Agent Memory coordinates external agents; it does not host or execute them.",
    "Multi-Agent Memory is source-available, not OSI open source, and no hosted-SaaS or production-at-scale adoption claim is made.",
    "Hash-only claims and bounded leases are cooperative controls for local .uai paths, not operating-system locks, merge engines, distributed consensus, or general source-code locks.",
    "UAIX/.uai is a typed continuity and handoff model; it is not a runtime orchestrator, hosted message queue, automatic synchronization engine, repository writer, or certification authority.",
    "The portfolio demonstrates runtime, integration, memory, governance, and tooling work around models; it does not claim foundation-model training or research breakthroughs.",
    "Confidential professional examples stay generic and do not disclose client names, prompts, data, infrastructure, volumes, financial outcomes, or private implementation details."
  ]
}