MasteryMade · Distribution PRD

PRD 8: Content Machine + Syndication

8.1 Purpose

End-to-end content production and distribution. Rubric-scored briefs → content in expert's voice → human review → scheduled publish → performance monitoring → re-ingest → rubric refines → next batch better. Dogfooded on MasteryMade first, then templated for every JV.

8.2 Pipeline

Marketing Rubric (PRD 5)
  → Content briefs (what to create, hook, format)
    → Generator (Module 2 voice + Module 4 frameworks)
      → Auto-score (rubric check before human sees it)
        → Review queue (approve / edit / reject)
          → Scheduled publish (autoposter)
            → Performance monitoring
              → Re-ingest metrics (universal ingest)
                → Rubric refinement (loop closes)

8.3 Content Brief Schema

{
  "brief_id":"UUID", "expert_id":"UUID",
  "content_type": "social_post|email|blog|video_script|lead_magnet|ad_copy",
  "platform": "instagram|linkedin|x|youtube|email|nowpage",
  "topic":"", "hook_pattern":"pain_agitation|curiosity_gap|contrarian|story_open",
  "framework_to_use":"Module 4 ref", "target_avatar":"ICP ref from PRD 5",
  "format_spec":{ "max_words":200, "include_cta":true, "visual_needed":true },
  "rubric_target_score": 7.5, "deadline":"2026-03-28",
  "status": "drafted|reviewing|approved|scheduled|published|measured"
}

8.4 Social Autoposter

Schema: scheduled_posts

CREATE TABLE scheduled_posts (
  id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
  brief_id UUID, expert_id UUID NOT NULL REFERENCES entities(id),
  platform TEXT NOT NULL, content_text TEXT NOT NULL,
  media_urls TEXT[], scheduled_for TIMESTAMPTZ NOT NULL,
  published_at TIMESTAMPTZ,
  status TEXT DEFAULT 'scheduled' CHECK (status IN ('draft','reviewing','approved','scheduled','published','failed')),
  platform_post_id TEXT, performance JSONB,
  created_at TIMESTAMPTZ DEFAULT now()
);

Platform adapters

Approval flow

Generated → auto-scored → if score ≥ target: move to reviewing → Jason reviews in dashboard or Telegram (approve/edit/reject) → approved → scheduled at optimal posting time → published → metrics collection begins.

Optimal posting time

Analyze Gate 4 competitor posting cadence + engagement. Cross-reference with expert's audience active times from platform insights. Schedule in optimal windows.

8.5 Email Sequence Generator

Template per expert: sequence name, trigger, emails with delay, subject template, body template, framework ref, CTA type, viral loop step.

8.6 AI Video Pipeline

Content Brief (video_script)
  → Script Generator (expert voice + framework)
    → HeyGen/Synthesia API: avatar video
      → Auto-captions
        → Thumbnail (Canva MCP or template)
          → YouTube upload
            → Auto-cut clips (60s/30s/15s)
              → IG Reels, TikTok, X, Shorts

Avatar: HeyGen custom or stock + ElevenLabs voice clone from expert recordings. Script from content brief + Module 2 voice. Long-form (5-15min) for YouTube, auto-cut social clips.

8.7 Mastery Labs Content Matrix

{
  "content_pillars": [
    { "name":"Core Framework Teaching", "frequency":"2x/week",
      "platforms":["linkedin","youtube"], "format":"long_form",
      "framework_rotation":["A","B","C"], "briefs_per_month":8 },
    { "name":"Quick Tips / Micro-Content", "frequency":"daily",
      "platforms":["instagram","x"], "format":"carousel|short_video",
      "source":"extract micro-insights from long-form", "briefs_per_month":20 },
    { "name":"Social Proof / Case Studies", "frequency":"1x/week",
      "platforms":["all"], "format":"story|testimonial",
      "source":"client results + Module 8", "briefs_per_month":4 },
    { "name":"Lead Magnet Promotion", "frequency":"2x/month",
      "platforms":["linkedin","email"], "format":"value_teaser + link",
      "source":"NowPage playbooks + tools", "briefs_per_month":2 }
  ],
  "promotion_calendar": { "generated_from":"pillars", "scheduling":"auto", "review":"weekly Sunday" }
}

8.8 Performance Feedback Loop

n8n cron every 6h: for each published post (>24h old) → call platform API → update performance JSONB → create content record in universal ingest (source_type='social', gate=3) with engagement metrics → trigger rubric rescoring if significant data → compare predicted vs actual → adjust weights if bias → increment rubric version.

8.9 Acceptance Criteria

• Content brief generation from rubric recommendations
• Content generation in expert voice (Module 2 validated)
• Auto-scoring before human review
• At least one autoposter working (LinkedIn first)
• Human review queue (Telegram or dashboard)
• Scheduled publishing at optimal times
• Metrics collection from at least one platform
• Metrics re-ingesting into universal content service
• Email sequence template for at least one expert
• Viral loop step in every sequence
• Mastery Labs matrix populated for MasteryMade
• Promotion calendar auto-generating from pillars