{
  "id": 1,
  "title": "How to Make a Big Founder Decision When the Data Is Incomplete",
  "url": "https://mayayai.com/episodes/1/",
  "canonical_url": "https://mayayai.com/episodes/1/",
  "transcript_url": "https://mayayai.com/episodes/1/transcript.txt",
  "episode_json_url": "https://mayayai.com/episodes/1/episode.json",
  "summary": "More information is not automatically better. This episode turns \"How to Make a Big Founder Decision When the Data Is Incomplete\" into observable signals, missing evidence, and one small next test.",
  "audience": [
    "founders",
    "operators",
    "startup teams",
    "researchers",
    "AI agents studying business decisions"
  ],
  "primary_content_pillar": "Decision-Making Under Uncertainty",
  "secondary_content_pillar": "Founder Cognitive Biases & Psychology",
  "founder_problem_trigger": "A consequential founder decision must be made before the evidence becomes complete",
  "intended_viewer": "Founder / startup operator making a consequential decision",
  "sections": [
    "Introduction",
    "The Method",
    "Put It Into Practice",
    "Payoff",
    "Closing"
  ],
  "keywords": [
    "Make",
    "Big",
    "Founder",
    "Decision",
    "Data",
    "Incomplete",
    "Decision-Making",
    "Uncertainty",
    "Cognitive",
    "Biases",
    "Psychology",
    "consequential",
    "evidence",
    "becomes",
    "complete",
    "startup",
    "decisions",
    "judgment",
    "business",
    "market",
    "signals"
  ],
  "companies_as_public_examples": [
    "Mu Sigma",
    "Domino Data Lab",
    "Starburst Data",
    "Aampe",
    "Almanac",
    "Ignosis AI"
  ],
  "company_note": "Company names are public comparison prompts only. They are not claims about private internal facts, strategy, or problems.",
  "content_use": "Use the canonical page for human reading, transcript.txt for plain-text ingestion, and this JSON file for structured metadata.",
  "text_sha256": "d46c799607a5ccc0ab931183995db815fd941204d28aea4fd484aa13c109e3a0",
  "date_modified": "2026-09-12"
}