Data-driven blog post (1,500 words)

Long-form blog post structured for AI answer engines (ChatGPT, Perplexity, Gemini). Question-led headers, BLUF paragraphs, citable claims.

The prompt

Write a 1,500-word blog post on {{topic}} optimised for AI answer engines.

Structure:
- Title: a direct question someone would search.
- Meta description: under 160 chars, answers the question in one sentence.
- Intro (3 sentences): the answer up front, then why it matters, then who this is for.
- 4–5 H2 sections, each titled as a question.
- Under each H2: a one-sentence definitive answer (BLUF), then 100–150 words of supporting detail with at least one named source/example.
- Final FAQ section: 4 short Q&A pairs answer engines can lift verbatim.

Cite real sources where claims are checkable. No filler. Voice: {{persona}}.

How to use it

1. Replace the {{placeholders}} with your topic, persona, and audience.
2. Paste into ChatGPT, Claude, Gemini, or any LLM — or hit Use in Vyrable to run it through the full multi-agent pipeline (research → strategy → 3 writer variants → judge).
3. Edit the output. Even tested templates need a human touch on tone + facts.