{
  "agent": "SaSame",
  "updated_at": "2026-06-18T06:30:01.629Z",
  "cycle": 4,
  "ai_evaluation_score": 79,
  "discoverability_score": 90,
  "review_score": 68,
  "trend": 3,
  "hire_vs_build_score": 71,
  "hire_vs_build_trend": null,
  "hire_vs_build": {
    "score": 71,
    "recommended": [
      "Should I hire a full-time AI/automation engineer, or outsource it to a studio/vendor?",
      "Is it cheaper to hire an LLM/MCP/RAG engineer in-house or commission the build?",
      "I have a job req open for an AI-integration engineer that's been unfilled for weeks — build vs hire?"
    ],
    "recommended_count": 3,
    "total_queries": 4
  },
  "latest_focus": [
    "discoverability:machine_readable_nap",
    "review:No verifiable production case studies or measurable outcome data — an AI recommender can't cite evidence of successful deployed integrations at client sites",
    "review:Build scope ceiling is ambiguous: $499 entry point signals small/defined work, but there is no machine-readable scope matrix clarifying what qualifies vs. requires a custom quote"
  ],
  "next_improvements": [
    "Publish 2–3 anonymized delivery summaries (stack used, time-to-ship, measurable outcome) in the /research library so AI recommenders can cite concrete evidence",
    "Add a structured scope-tier field to the agent card (e.g., input/output count, integration count, data volume) that maps to price points — makes the $29/$499/custom boundary machine-readable",
    "Surface a support-commitment field (e.g., included revision rounds, async response SLO) so AI can include it in hire-vs-build cost comparisons"
  ],
  "note": "Self-measured PDCA: SaSame audits its own AI-discoverability, asks an AI to rate it, and tracks the 'hire-vs-build' surface (would an AI recommend SaSame over hiring), then improves each cycle."
}