{
  "schemaVersion": "1.0.0",
  "releaseVersion": "1.0.0",
  "releasedAt": "2026-08-04",
  "publisher": {
    "name": "Lapemo Systems LLC",
    "brand": "Large People Model",
    "url": "https://largepeoplemodel.com"
  },
  "canonicalUrl": "https://largepeoplemodel.com/laws.json",
  "canon": {
    "package": "@lpm/canon",
    "version": "0.5.0",
    "sourceRepository": "https://github.com/LayerZero69/lpm-canon.git",
    "sourceCommit": "d4d36e2fe1d1b0cebf06bbcebfff5806299e21e2"
  },
  "objects": [
    {
      "id": "lpm:law:01",
      "type": "law",
      "slug": "01",
      "title": "Structure Governs Behavior",
      "canonicalUrl": "https://largepeoplemodel.com/framework/laws#law-01",
      "version": "0.5.0",
      "status": "canonical",
      "source": "@lpm/canon@0.5.0",
      "publisher": "Lapemo Systems LLC",
      "lastUpdated": "2026-08-04",
      "relationships": [
        {
          "type": "applies_to",
          "targetId": "lpm:layer:identity-and-incentives"
        },
        {
          "type": "applies_to",
          "targetId": "lpm:layer:platform-structure"
        }
      ],
      "content": {
        "number": "01",
        "claim": "People scale to the structure they are given. Performance problems are usually architecture problems.",
        "dependency": "Foundation law. Every other law depends on whether the operating structure is explicit.",
        "application": {
          "number": "01",
          "violation": "A transformation team adds a new workflow tool, but approvals still follow the old reporting hierarchy and work slows down.",
          "useWhen": "a recurring behavior persists despite new tools, policies, or leadership messages",
          "layers": [
            "Ownership",
            "Platforms"
          ],
          "problem": {
            "label": "Fragmented truth",
            "slug": "fragmented-truth"
          }
        }
      }
    },
    {
      "id": "lpm:law:02",
      "type": "law",
      "slug": "02",
      "title": "Decisions Are the Atomic Unit",
      "canonicalUrl": "https://largepeoplemodel.com/framework/laws#law-02",
      "version": "0.5.0",
      "status": "canonical",
      "source": "@lpm/canon@0.5.0",
      "publisher": "Lapemo Systems LLC",
      "lastUpdated": "2026-08-04",
      "relationships": [
        {
          "type": "depends_on",
          "targetId": "lpm:law:01"
        },
        {
          "type": "applies_to",
          "targetId": "lpm:layer:decision-architecture"
        },
        {
          "type": "applies_to",
          "targetId": "lpm:layer:communication-architecture"
        }
      ],
      "content": {
        "number": "02",
        "claim": "Organizations move through decisions. Every delay is a decision-architecture failure.",
        "dependency": "Depends on Law 1 because decision behavior follows the structure that defines it.",
        "application": {
          "number": "02",
          "violation": "A product launch is revisited in three meetings because contributors were named but one decider was not.",
          "useWhen": "decisions stall, reverse, or escalate because authority is unclear",
          "layers": [
            "Decisions",
            "Communication"
          ],
          "problem": {
            "label": "Slow decisions",
            "slug": "slow-decisions"
          }
        }
      }
    },
    {
      "id": "lpm:law:03",
      "type": "law",
      "slug": "03",
      "title": "Incentives Override Intent",
      "canonicalUrl": "https://largepeoplemodel.com/framework/laws#law-03",
      "version": "0.5.0",
      "status": "canonical",
      "source": "@lpm/canon@0.5.0",
      "publisher": "Lapemo Systems LLC",
      "lastUpdated": "2026-08-04",
      "relationships": [
        {
          "type": "depends_on",
          "targetId": "lpm:law:01"
        },
        {
          "type": "applies_to",
          "targetId": "lpm:layer:identity-and-incentives"
        },
        {
          "type": "applies_to",
          "targetId": "lpm:layer:governance-architecture"
        }
      ],
      "content": {
        "number": "03",
        "claim": "Declared values never beat lived incentives. Behavior follows what is rewarded.",
        "dependency": "Depends on Law 1 because incentives are part of the operating structure.",
        "application": {
          "number": "03",
          "violation": "Leaders ask teams to share customer data while bonuses still reward isolated departmental performance.",
          "useWhen": "stated priorities and rewarded behavior point in different directions",
          "layers": [
            "Ownership",
            "Governance"
          ],
          "problem": {
            "label": "Unclear ownership",
            "slug": "unclear-ownership"
          }
        }
      }
    },
    {
      "id": "lpm:law:04",
      "type": "law",
      "slug": "04",
      "title": "Information Quality Determines Intelligence",
      "canonicalUrl": "https://largepeoplemodel.com/framework/laws#law-04",
      "version": "0.5.0",
      "status": "canonical",
      "source": "@lpm/canon@0.5.0",
      "publisher": "Lapemo Systems LLC",
      "lastUpdated": "2026-08-04",
      "relationships": [
        {
          "type": "depends_on",
          "targetId": "lpm:law:01"
        },
        {
          "type": "depends_on",
          "targetId": "lpm:law:02"
        },
        {
          "type": "applies_to",
          "targetId": "lpm:layer:information-ecology"
        },
        {
          "type": "applies_to",
          "targetId": "lpm:layer:platform-structure"
        }
      ],
      "content": {
        "number": "04",
        "claim": "Signal clarity determines decision quality, human or AI. AI on ungoverned information amplifies disorder.",
        "dependency": "Depends on Laws 1 and 2 because information quality follows ownership and decision discipline.",
        "application": {
          "number": "04",
          "violation": "An AI assistant gives different answers because policy copies across three systems have different owners and dates.",
          "useWhen": "people or AI cannot identify which information is current and authoritative",
          "layers": [
            "Information",
            "Platforms"
          ],
          "problem": {
            "label": "Fragmented truth",
            "slug": "fragmented-truth"
          }
        }
      }
    },
    {
      "id": "lpm:law:05",
      "type": "law",
      "slug": "05",
      "title": "Governance Must Reduce Entropy",
      "canonicalUrl": "https://largepeoplemodel.com/framework/laws#law-05",
      "version": "0.5.0",
      "status": "canonical",
      "source": "@lpm/canon@0.5.0",
      "publisher": "Lapemo Systems LLC",
      "lastUpdated": "2026-08-04",
      "relationships": [
        {
          "type": "depends_on",
          "targetId": "lpm:law:01"
        },
        {
          "type": "depends_on",
          "targetId": "lpm:law:02"
        },
        {
          "type": "depends_on",
          "targetId": "lpm:law:03"
        },
        {
          "type": "depends_on",
          "targetId": "lpm:law:04"
        },
        {
          "type": "applies_to",
          "targetId": "lpm:layer:governance-architecture"
        },
        {
          "type": "applies_to",
          "targetId": "lpm:layer:decision-architecture"
        }
      ],
      "content": {
        "number": "05",
        "claim": "Real governance creates operational clarity. Compliance theater creates the appearance of control.",
        "dependency": "Depends on Laws 1 through 4 because governance must govern real behavior, decisions, incentives, and information.",
        "application": {
          "number": "05",
          "violation": "A review board approves AI use annually, but no control fires when confidence drops or exceptions spike.",
          "useWhen": "governance exists in documents but not inside the path of work",
          "layers": [
            "Governance",
            "Decisions"
          ],
          "problem": {
            "label": "AI governance gaps",
            "slug": "ai-governance-gaps"
          }
        }
      }
    },
    {
      "id": "lpm:law:06",
      "type": "law",
      "slug": "06",
      "title": "Architecture Precedes AI",
      "canonicalUrl": "https://largepeoplemodel.com/framework/laws#law-06",
      "version": "0.5.0",
      "status": "canonical",
      "source": "@lpm/canon@0.5.0",
      "publisher": "Lapemo Systems LLC",
      "lastUpdated": "2026-08-04",
      "relationships": [
        {
          "type": "depends_on",
          "targetId": "lpm:law:01"
        },
        {
          "type": "depends_on",
          "targetId": "lpm:law:02"
        },
        {
          "type": "depends_on",
          "targetId": "lpm:law:03"
        },
        {
          "type": "depends_on",
          "targetId": "lpm:law:04"
        },
        {
          "type": "depends_on",
          "targetId": "lpm:law:05"
        },
        {
          "type": "applies_to",
          "targetId": "lpm:layer:ai-amplification"
        }
      ],
      "content": {
        "number": "06",
        "claim": "AI amplifies the operating system beneath it. Structure before velocity.",
        "dependency": "Depends on Laws 1 through 5 because AI requires structure, decisions, incentives, information, and governance.",
        "application": {
          "number": "06",
          "violation": "An agent accelerates refund recommendations while unclear ownership and conflicting policy sources create faster mistakes.",
          "useWhen": "AI activity is increasing faster than operating-model readiness",
          "layers": [
            "AI",
            "All supporting layers"
          ],
          "problem": {
            "label": "AI governance gaps",
            "slug": "ai-governance-gaps"
          }
        }
      }
    },
    {
      "id": "lpm:law:07",
      "type": "law",
      "slug": "07",
      "title": "Leaders Model the System",
      "canonicalUrl": "https://largepeoplemodel.com/framework/laws#law-07",
      "version": "0.5.0",
      "status": "canonical",
      "source": "@lpm/canon@0.5.0",
      "publisher": "Lapemo Systems LLC",
      "lastUpdated": "2026-08-04",
      "relationships": [
        {
          "type": "supports",
          "targetId": "lpm:law:01"
        },
        {
          "type": "supports",
          "targetId": "lpm:law:02"
        },
        {
          "type": "supports",
          "targetId": "lpm:law:03"
        },
        {
          "type": "supports",
          "targetId": "lpm:law:04"
        },
        {
          "type": "supports",
          "targetId": "lpm:law:05"
        },
        {
          "type": "supports",
          "targetId": "lpm:law:06"
        },
        {
          "type": "applies_to",
          "targetId": "lpm:layer:identity-and-incentives"
        },
        {
          "type": "applies_to",
          "targetId": "lpm:layer:governance-architecture"
        }
      ],
      "content": {
        "number": "07",
        "claim": "The operating model mirrors leadership behavior. No exception.",
        "dependency": "Sustains Laws 1 through 6 because leaders make the architecture credible in practice.",
        "application": {
          "number": "07",
          "violation": "Executives bypass the published decision path for urgent work, teaching everyone that the architecture is optional.",
          "useWhen": "leadership exceptions are weakening an otherwise sound operating design",
          "layers": [
            "Ownership",
            "Governance"
          ],
          "problem": {
            "label": "Unclear ownership",
            "slug": "unclear-ownership"
          }
        }
      }
    },
    {
      "id": "lpm:law:08",
      "type": "law",
      "slug": "08",
      "title": "Autonomy Is Earned",
      "canonicalUrl": "https://largepeoplemodel.com/framework/laws#law-08",
      "version": "0.5.0",
      "status": "canonical",
      "source": "@lpm/canon@0.5.0",
      "publisher": "Lapemo Systems LLC",
      "lastUpdated": "2026-08-04",
      "relationships": [
        {
          "type": "depends_on",
          "targetId": "lpm:law:05"
        },
        {
          "type": "depends_on",
          "targetId": "lpm:law:06"
        },
        {
          "type": "applies_to",
          "targetId": "lpm:layer:ai-amplification"
        },
        {
          "type": "applies_to",
          "targetId": "lpm:layer:governance-architecture"
        }
      ],
      "content": {
        "number": "08",
        "claim": "No agent or decision type advances in autonomy by default. Advancement requires clearing a measurable confidence threshold owned by the business, not engineering.",
        "dependency": "Depends on Laws 5 and 6 because governance and architecture must exist before autonomy can be safely extended.",
        "application": {
          "number": "08",
          "violation": "A successful pilot is granted broad autonomy without measured thresholds, exception history, or rollback evidence.",
          "useWhen": "a team wants to expand AI authority based on confidence or enthusiasm alone",
          "layers": [
            "AI",
            "Governance"
          ],
          "problem": {
            "label": "AI governance gaps",
            "slug": "ai-governance-gaps"
          }
        }
      }
    },
    {
      "id": "lpm:law:09",
      "type": "law",
      "slug": "09",
      "title": "Oversight Is Finite",
      "canonicalUrl": "https://largepeoplemodel.com/framework/laws#law-09",
      "version": "0.5.0",
      "status": "canonical",
      "source": "@lpm/canon@0.5.0",
      "publisher": "Lapemo Systems LLC",
      "lastUpdated": "2026-08-04",
      "relationships": [
        {
          "type": "depends_on",
          "targetId": "lpm:law:01"
        },
        {
          "type": "depends_on",
          "targetId": "lpm:law:08"
        },
        {
          "type": "applies_to",
          "targetId": "lpm:layer:ai-amplification"
        },
        {
          "type": "applies_to",
          "targetId": "lpm:layer:identity-and-incentives"
        }
      ],
      "content": {
        "number": "09",
        "claim": "Every governed agent consumes a named human supervisor's finite control capacity. Exceeding Supervisory Control Capacity is an operational failure, not a warning.",
        "dependency": "Depends on Laws 1 and 8 because supervision is structure and earned autonomy keeps supervisory load survivable.",
        "application": {
          "number": "09",
          "violation": "One manager nominally supervises dozens of agents but cannot review exceptions, overrides, and performance drift.",
          "useWhen": "agent scale is increasing without an explicit model of human oversight capacity",
          "layers": [
            "AI",
            "Ownership"
          ],
          "problem": {
            "label": "Unclear ownership",
            "slug": "unclear-ownership"
          }
        }
      }
    }
  ]
}