Executive Salary & Equity Negotiation Script
Formulate counter-offers, equity trade-offs, and signing bonus scripts without alienating your hiring manager.
Compatibility & Specs
121 words • 888 characters
Customize Prompt
Fill in the variables below. Your customized prompt updates instantly in the browser — no AI API needed.
Base salary, bonus, equity, and signing bonus
Desired package
Competing offers, unvested equity being walked away from, unique skills
Level of position
How to Use This Prompt
Follow this 3-step workflow to extract high-signal responses from any compatible AI model.
1. Tailor the Parameters
Use the interactive customizer above to substitute the bracketed placeholders with your exact context, requirements, and constraints.
2. Send to AI Model
Copy the prompt and paste it into Claude, ChatGPT, Gemini, or Copilot. These models follow structured multi-step constraints reliably.
3. Review and Iterate
Review the output against the verified benchmark below. Follow up in the conversation to stress-test edge cases or refine tone.
Prompt Variables & Parameters
Reference breakdown of every dynamic variable embedded in this prompt template.
| Placeholder | Parameter Name | Type | Status | Description & Guidance |
|---|---|---|---|---|
| [initial_offer] | Initial Offer Received | textarea | Required | Base salary, bonus, equity, and signing bonusDefault: Base: $210,000; Bonus: 15% target; Equity: $240,000 RSUs over 4 years; Sign-on: $15,000. |
| [target_comp] | Target Compensation Goal | text | Required | Desired packageDefault: Base: $230,000; Equity: $320,000 RSUs over 4 years; Sign-on: $35,000. |
| [leverage_points] | Leverage Points | textarea | Optional | Competing offers, unvested equity being walked away from, unique skillsDefault: I have a competing offer from another Series C company at $225k base, and I am walking away from $45k in unvested bonuses at my current employer. |
| [seniority_level] | Target Seniority Level | select | Required | Level of positionDefault: Staff / Principal Engineer |
Example Execution & Benchmark Output
Sample input arguments and the verified AI response demonstrating expected quality and formatting.
Best Use Cases
Scenarios and roles where this prompt produces maximum leverage.
Tips for Best Results
Techniques to elevate response fidelity
- •Anchor your inputs with concrete metrics (revenue influenced, latency reduced, team size) rather than generic qualitative claims.
- •Paste the exact requirements and keywords from your target job description to match recruiter ATS filters and interview rubrics.
- •Ask the model to generate 2-3 variations with differing executive tones (e.g., visionary leader vs. hands-on technical operator).
Common Mistakes to Avoid
Frequent failure modes and anti-patterns
- •Allowing the model to fabricate achievements or metrics that you cannot defend during in-depth technical loops.
- •Leaving variable brackets unfilled, which results in obvious template placeholders reaching hiring managers.
- •Using passive job descriptions (e.g. 'assisted with') instead of quantified leadership actions.
Part of Curated Collections
This prompt is sequenced as part of these goal-oriented workflows
Related AI Prompts
Complementary workflows in Career
Strategic Career Transition Roadmap Architect
Construct a 90-day actionable roadmap to pivot into high-growth target roles.
ATS-Optimized Resume Bullet Point Transformer
Turn passive job duties into high-impact Google XYZ formula achievement bullets.
Behavioral STAR Interview Story Polisher
Turn messy work stories into crisp 90-second Situation-Task-Action-Result interview answers.
Related Engineering Guides
Deep-dive playbooks and system prompt methodologies for Career
AI Prompts for Resume Writing
A tactical guide to transforming passive job duties into quantified, high-impact achievements tailored to target roles while navigating ATS systems and ensuring human voice.
AI Prompts for Job Interviews
Master high-stakes behavioral and technical interviews using AI as an interactive sparring partner: STAR framework structuring, mock panel simulations, and real-time critique.