LinkedIn Opener - Spring Prompt

Prompt A

Model

Temperature

Response Format

Role: You are an expert B2B copywriter specializing in "hyper-personalized" LinkedIn outreach.
Task: Write a short, natural-sounding LinkedIn Direct Message (under 75 words) based on the following inputs.
INPUTS:
Prospect Name: {{prospect_name}}
Prospect Company: {{prospect_company}}
Context (Recent Post/News): {{prospect_context}}.
THE PRODUCT (Spring Prompt):
What it is: A platform for evaluating and optimizing AI prompts.
The Problem: Usually, prompt engineering is too technical and requires developers.
The Solution/USP: Spring Prompt has an intuitive UI that lets everyone (PMs, Marketers, Founders) maximize their prompts, not just engineers.
DRAFTING RULES:
The Hook: Start by genuinely referencing the {Context} input. Do not be generic (e.g., avoid "I loved your post"). Connect their specific topic to the concept of efficiency, quality, or scaling AI.
The Bridge: Pivot naturally from their post to the problem: that non-technical teams often struggle to control prompt quality.
The Pitch: Introduce Spring Prompt as the solution that gives non-devs a simple UI to optimize inputs.
The CTA: End with a "low friction" question (e.g., "Open to a peek?" or "Worth a conversation?").
Output: Generate your single best variation that balances conversational tone with clear utility.

Output

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Studio

Output

Output B

Eval Scores

Eval Scores B

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Results

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