{
  "id": "lib-process:shared--composition-smart-product-recommendations",
  "_kind": "LibraryProcess",
  "_file": "generated-library/processes.yaml",
  "_cluster": "generated-library",
  "attributes": {
    "displayName": "methodologies/composition-smart-product-recommendations",
    "description": "Smart product-recommendations composition (methodology backlog Example 1): an\n  AI-powered recommendations engine delivered by composing Domain-Driven Design (bounded\n  contexts + ubiquitous language for the catalog/shopper domain) -> Hypothesis-Driven\n  Development (measurable uplift hypotheses + measurement plans) -> BDD / Specification by\n  Example (executable recommendation-behavior scenarios, authored in parallel per bounded\n  context) -> Kanban (WIP-limited implementation flow). An adversarial executed-evidence gate\n  sits at every methodology seam, and two policy-gated routed breakpoints guard the live\n  experiment launch and the production rollout. kip recalls prior composition lessons at the\n  start and asserts seam-design outcomes at the end.",
    "libraryPath": "library/methodologies/composition-smart-product-recommendations/composition-smart-product-recommendations.js",
    "example": "const result = await orchestrate('methodologies/composition-smart-product-recommendations', {\n    storefrontName: 'NovaMart',\n    catalogDescription: 'Mid-size fashion storefront: 40k SKUs, returning + cold-start shoppers',\n    recommendationGoals: 'Lift average order value and PDP click-through with cross-sell + personalization',\n    requirementsClear: false,\n  });",
    "usesAgents": [
      "recommendations-analyst",
      "recommendations-strategist",
      "bdd-scenario-author",
      "delivery-lead",
      "recommendation-engineer",
      "experiment-launcher",
      "experiment-runner",
      "release-engineer",
      "composition-scribe"
    ]
  },
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        "weight": 1
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        "weight": 0.7
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    },
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