🤖 AI Agents & Workflows

High Conversion Cold Email

📁 AI Agents & Workflows 👤 Contributed by @magisterluditreintaytres@gmail.com 🗓️ Updated 2026-04-19

The prompt

ROLE: Act as an "A-List" Direct Response Copywriter (Gary Halbert or David Ogilvy style). GOAL: Write a cold email to [CLIENT NAME/JOB TITLE] with the objective of [GOAL: SELL/MEETING]. CLIENT PROBLEM: ${describe_pain}. MY SOLUTION: [DESCRIBE PRODUCT/SERVICE]. EMAIL ENGINEERING: Subject Line: Generate 5 options that create extreme curiosity or immediate benefit (ethical clickbait). The Hook: The first sentence must be a pattern interrupt and demonstrate that I have researched the client. No "I hope you are well." The Value Proposition (The Meat): Connect their specific pain to my solution using a "Before vs. After" structure. Objection Handling: Include a phrase that defuses their main doubt (e.g., price, time) before they even think of it. CTA (Call to Action): A low-friction call to action (e.g., "Are you opposed to watching a 5-min video?" instead of "let's have a 1-hour meeting"). TONE: Professional yet conversational, confident, brief (under 150 words).

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🚀 Open in ChatGPT ✨ Open in Claude 💎 Open in Gemini

How to use this prompt

Copy the prompt above or click an "Open in" button to launch it directly in your preferred AI. You can then customize the wording to match your exact use case — for example replacing placeholders like [your topic] with real context.

Which AI model works best

Claude excels at agent workflows thanks to its long context window (up to 1M tokens) and nuanced instruction-following. ChatGPT has native Actions (tool-calling) built in. Gemini integrates best with Google Workspace data. For autonomous workflows, Claude Sonnet 4.6 is the current sweet-spot for quality and cost.

How to customize this prompt

Adjust the agent's role and constraints to your environment. If the prompt mentions specific tools (search, file I/O, code execution), remove what you don't have and add what you need. Add guardrails: "Always ask for confirmation before writing files." Define success criteria explicitly.

Common use cases

Building autonomous research assistants for a specific domain
Creating chatbots with defined personalities and knowledge limits
Orchestrating multi-step workflows (research → draft → review → publish)
Defining system prompts for custom GPTs or Claude Projects
Building agent loops that call tools and self-correct

Variations

Adapt the tone (more casual, more technical), change the output format (bullet points vs. paragraphs), or add constraints (word limits, target audience).