Content Lifecycle

The pipeline doesn't stop at finding opportunities. It generates briefs, drafts full articles, and tracks outcomes after publishing. Each step feeds the next.

The lifecycle

1. Action Queue

After the pipeline runs, opportunities are ranked into an action queue. Each queue item has:

• Priority score — from opportunity scoring
• Kind — opportunity (content to create) or insight (brand issue to fix)
• Status — pending, in_progress, or done

Fetch it with GET /brands/{id}/queue. Items are pre-sorted by priority — start from the top.

2. Brief Generation

Pick a queue item and generate a content brief:

curl -s -X POST \
  -H "X-API-Key: $BM_API_KEY" \
  -H "Content-Type: application/json" \
  "https://api.boringmarketing.com/brands/$BRAND_ID/brief" \
  -d '{"queue_item_id": "queue-uuid-here"}'

The brief engine (Sonnet) produces a structured blueprint:

• Target keyword strategy
• Content outline with H2/H3 hierarchy
• Section-by-section guidance
• Brand context injection (voice, terminology, trust signals from enrichment)
• Internal linking recommendations
• Competitive angle

If brand enrichment ran earlier, the brief includes your specific trust signals, certifications, and terminology — not generic filler.

3. Content Drafting

Turn a brief into a full article:

curl -s -X POST \
  -H "X-API-Key: $BM_API_KEY" \
  -H "Content-Type: application/json" \
  "https://api.boringmarketing.com/brands/$BRAND_ID/execute" \
  -d '{"brief_id": "brief-uuid-here"}'

The content agent (Opus) drafts the article using the brief plus brand facts from the enrichment crawl. No re-crawling — it reuses the data already collected.

4. Outcome Tracking

After publishing, log the URL so the system can track its performance:

curl -s -X POST \
  -H "X-API-Key: $BM_API_KEY" \
  -H "Content-Type: application/json" \
  "https://api.boringmarketing.com/track/outcomes/report" \
  -d '{
    "brand_id": "'$BRAND_ID'",
    "recommendation_id": "opp-uuid",
    "event_type": "completed",
    "notes": "Published at https://yourdomain.com/article"
  }'

The system monitors at three milestones:

5. The Learning Loop

Outcome data feeds back into the scoring system. The infrastructure is live today: outcome events are logged, tracking snapshots capture rankings + citations at the time of publish, and /track/brands/{id}/changes?since= computes deltas between any two snapshots.

After enough outcomes are collected:

• Opportunities that consistently produce citations get higher priority
• Formats that perform better for your industry get recommended more often
• Leverage scoring multipliers get calibrated from real results instead of the baseline heuristics

This is the compounding advantage: every piece of content you publish makes the next recommendation more accurate. See the Tracking Outcomes guide for the full snapshot + changes + outcome-report workflow.