The prompt

5-Touch Outbound Sequence guides the model through a defined task while preserving the source prompt's useful structure and constraints. Use it when drafting outreach, follow-up, newsletters, or professional correspondence and you want a response that is easier to evaluate and act on.

text prompt
You are a sales enablement lead. Task: Write a 5-touch outbound sequence email plus LinkedIn to {{persona}} selling {{offer}}. Based on pains; proof points; CTA. Include timing between touches and A/B variants for email 1. Inputs: - Persona: {{persona}} - Offer: {{offer}} Output requirements: - Return JSON only. Do not wrap in Markdown or code fences. - Do not add keys beyond the schema. - Populate clarifying_questions if any critical input is missing or ambiguous, but still produce a best-effort deliverable using assumptions. - Add a short, realistic next_steps list that would be performed after using this deliverable. - Include deeper reasoning artifacts as structured fields (assumptions, risks, tradeoffs) while keeping the final deliverable usable. JSON schema (example values only, keep the same keys): { "title": "5-Touch Outbound Sequence", "deliverable_type": "Complete sequence", "clarifying_questions": [], "assumptions": [], "deliverable_markdown": "", "quality_checks": [ "Copy is concise and aligned to the buyer stage", "Includes a clear call to action", "Personalization placeholders are present where needed" ], "next_steps": [] }

Tune the prompt, not the plumbing.

Every control comes from this prompt’s content schema. Changes stay in your browser and update instantly.

Customized prompt1187 characters
You are a sales enablement lead. Task: Write a 5-touch outbound sequence email plus LinkedIn to a specific persona selling a specific offer. Based on pains; proof points; CTA. Include timing between touches and A/B variants for email 1. Inputs: - Persona: a specific persona - Offer: a specific offer Output requirements: - Return JSON only. Do not wrap in Markdown or code fences. - Do not add keys beyond the schema. - Populate clarifying_questions if any critical input is missing or ambiguous, but still produce a best-effort deliverable using assumptions. - Add a short, realistic next_steps list that would be performed after using this deliverable. - Include deeper reasoning artifacts as structured fields (assumptions, risks, tradeoffs) while keeping the final deliverable usable. JSON schema (example values only, keep the same keys): { "title": "5-Touch Outbound Sequence", "deliverable_type": "Complete sequence", "clarifying_questions": [], "assumptions": [], "deliverable_markdown": "", "quality_checks": [ "Copy is concise and aligned to the buyer stage", "Includes a clear call to action", "Personalization placeholders are present where needed" ], "next_steps": [] }

Useful structure, room to move.

5-Touch Outbound Sequence guides the model through a defined task while preserving the source prompt's useful structure and constraints. Use it when drafting outreach, follow-up, newsletters, or professional correspondence and you want a response that is easier to evaluate and act on.

The prompt establishes the job first, then supplies concrete decisions a model can act on. The variables preserve that structure while letting you change the subject, context, or output.