Recommendation:
Build a Zapier pipeline that (1) reads calendar/keyword rows (Google Sheets or Calendar event → Zap trigger), (2) writes a ‘queued’ job row to a queue table (Airtable/Sheets), (3) sends a webhook to ChatGPT (via Zapier’s OpenAI app or Webhooks → OpenAI chat completions endpoint) with a strict JSON-output prompt, (4) validates the JSON, and (5) pushes the structured brief to your CMS. Use idempotency keys, status fields, and automatic retries.

Practical Zap layout (step-by-step):
- Trigger: New/Updated row in Google Sheets or new Calendar event.
- Action: Create job record in Queue (Airtable/Sheets) with request_id, status=queued, retry_count=0.
- Action: (Optional) Delay/Rate limiter step to control throughput (1 request per Xs).
- Action: Webhooks → POST to OpenAI Chat endpoint or Zapier OpenAI action. Include unique request_id and model params (temperature=0, max_tokens limit).
- Action: Code/Formatter step to validate/parse JSON. If invalid, call a “fix JSON” prompt or mark failed.
- Action: Update Queue row status=done (store output) and push to CMS (API or CMS Zap).
- Error paths: on failure increment retry_count, set status=retry_scheduled, schedule re-attempt (Delay + rerun) up to N attempts; on final fail set status=failed and notify Slack/email.

Prompt template (use system + user; force JSON and sentinel):
System: "You are an expert SaaS content strategist. Always respond only with JSON and nothing else. If you cannot fill a field, set it to null. End output with the line: ###END###."
User (single string with injected variables):
"Generate a content brief for: {title}
Primary keyword: {primary_keyword}
Supporting keywords: {keywords}
Target audience: {audience}
Tone: {tone}
Target word count: {word_count}
Return a JSON object with keys: title, primary_keyword, supporting_keywords (array), meta_description (<=155 chars), one_line_angle, persona, outline (array of {heading, type[h2/h3], intent, bullets}), required_internal_links (array), external_refs (array of URLs), CTA, and editorial_notes. Keep answers concise."
Example JSON schema to include in prompt so model follows structure.

Webhook patterns and reliability tips:
- Idempotency: send a unique request_id and store it in your queue; if Zap retries, reject duplicate processing by checking the id.
- Backoff & retries: implement exponential backoff (e.g., retry after 1m, 5m, 20m) and max_retries (3–5). Use Zapier Delay and conditional logic to reschedule.
- Response validation: require strict JSON with sentinel (###END###). Validate with a Code step (JavaScript/Python) and reject invalid responses.
- Queueing & pacing: use Airtable/Sheets as a queue if you need persistent state and to prevent bursts. Add a worker Zap that only processes X items/hour.
- Rate limits & costs: prefer deterministic prompts (temperature=0). Monitor token usage; consider smaller models (gpt-4o-mini or gpt-4 if quality needed) based on budget.
- Fallbacks for malformed output: second “repair” prompt instructing the model to fix JSON, then retry parsing once.

Decision criteria (help choose approach):
- Budget: use smaller models and batch content to lower cost. Zapier + OpenAI API costs scale with volume.
- Skill level: Zapier no-code + small code steps is fine; full webhook patterns and queueing benefit from dev resources.
- Team size/QA needs: if many briefs require heavy human edits, keep a manual QA column and human-in-the-loop step.
- Output quality: use higher-tier models and richer prompts (examples, reference briefs) for better briefs.

Practical checklist before go-live:
- Map input fields → variables in prompt.
- Build queue with status, request_id, retry_count.
- Implement webhook call with unique id and temperature=0.
- Implement JSON validation + sentinel check.
- Add retry/backoff and Slack/email alerts for failed jobs.
- Add human QA step for first N briefs to refine prompt.

Best-for / Avoid-if:
- Best for: teams producing 10–100 briefs/week that want deterministic, structured outputs with lightweight ops.
- Avoid if: you need highly creative, long-form research-heavy briefs that require significant human research—those need a heavier human-in-the-loop process.

If you want, I can paste a ready-to-use Zapier webhook payload + the exact ChatGPT prompt JSON and a small validation script to drop into a “Code by Zapier” step.

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