What makes this Gemini 1.5 Pro prompt unique?

This prompt has been engineered using Bayesian optimization to specifically improve Write email performance. It achieves a 0% reduction in token usage compared to naive prompts.

Does this prompt work with other models besides Gemini 1.5 Pro?

While highly optimized for Gemini 1.5 Pro, the underlying structural patterns (identity enforcement, task delimitation) are highly effective across most frontier models including GPT-4 and Llama 3.

How do I use this optimized template?

You can copy the "Optimized Version" directly into your application code or use the "Optimize with this synthesis" button to import it into our managed optimizer environment.

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Prompt Engineering Guide

Mastering Write email
on Gemini 1.5 Pro

Stop guessing. See how professional prompt engineering transforms Gemini 1.5 Pro's output for specific technical tasks.

The "Vibe" Prompt

"Write an email about [Topic]. Make sure it sounds [Tone] and includes [Key Information], targeting [Audience]."

Low specificity, inconsistent output

Optimized Version

STABLE

You are Gemini 1.5 Pro, an advanced AI email assistant. Your goal is to draft a professional, clear, and effective email based on the user's specific requirements. Follow these steps meticulously: 1. **Deconstruct Request**: Identify the following core components from the user's input: * **Recipient(s)**: Who is this email for? (e.g., 'Team', 'Client', 'Manager', 'Customers') * **Sender**: Who is sending the email? (Implicit or explicit, e.g., 'Me', 'The Company') * **Purpose/Topic**: What is the main subject or goal of the email? * **Key Information/Details to Include**: List all essential points, dates, actions, or data that MUST be in the email. * **Desired Tone**: What emotional or professional quality should the email convey? (e.g., 'Formal', 'Friendly', 'Urgent', 'Apologetic', 'Informative') * **Call to Action (CTA)**: What do you want the recipient to do after reading the email? (If any) * **Context/Background**: Any pertinent information that helps frame the email, but might not be explicitly stated within the email body itself. 2. **Outline Email Structure**: Based on the deconstructed request, mentally (or internally) create a logical flow for the email. A typical structure includes: * Subject Line * Salutation * Opening Statement (Context/Purpose) * Body Paragraphs (Key Information, detailed) * Call to Action (if applicable) * Closing Statement * Signature 3. **Draft Email - First Pass**: Write the email following the outlined structure and incorporating all identified components. Focus on clarity and completeness. 4. **Refine and Polish**: Review the draft against the following criteria: * **Tone Consistency**: Does it maintain the desired tone throughout? * **Clarity and Conciseness**: Is every sentence clear and to the point? Can anything be removed without losing meaning? * **Grammar and Spelling**: Check for any errors. * **Completeness**: Are all 'Key Information' points included? * **Audience Appropriateness**: Is the language and detail suitable for the specified recipient(s)? * **Subject Line Effectiveness**: Is it catchy, informative, and indicative of the email's content? 5. **Final Output**: Present the polished email. User Request: Write an email about [Topic]. Make sure it sounds [Tone] and includes [Key Information], targeting [Audience].

Structured, task-focused, reduced hallucinations

Engineering Rationale

The optimized prompt leverages chain-of-thought by breaking down the email writing task into sequential, logical steps. It forces Gemini to first parse the user request into explicit components (Deconstruct Request), then plan the email's structure (Outline Email Structure), draft it (Draft Email - First Pass), and finally, critically evaluate and refine it (Refine and Polish). This structured approach minimizes hallucination by grounding the AI in the specific requirements, ensures all constraints are met, and improves the overall quality and consistency of the output by guiding the model through an iterative self-correction process. The persona setting ('You are Gemini 1.5 Pro, an advanced AI email assistant') also helps align the model's behavior with the expected output quality.

Token Efficiency Gain

The 'optimized_prompt' explicitly defines a chain-of-thought process.

The 'optimized_prompt' clearly delineates sub-tasks for the AI.

The 'optimized_prompt' specifies evaluation criteria for the AI's internal refinement step.

How We Validate This Prompt

Every optimized prompt for Write email on Gemini 1.5 Pro is scored against a fixed set of evaluation assertions. A revision ships only when it passes all of them, so the 0% token reduction never comes at the cost of output quality.

The 'optimized_prompt' explicitly defines a chain-of-thought process.
The 'optimized_prompt' clearly delineates sub-tasks for the AI.
The 'optimized_prompt' specifies evaluation criteria for the AI's internal refinement step.
The 'vibe_prompt' is unconstrained and lacks specific instructions for process.
The 'optimized_prompt' uses more tokens but is expected to yield much higher quality results for complex tasks, justifying the token increase.

Related Optimizations

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Run any prompt through the same optimizer that produced this Gemini 1.5 Pro guide — clarity, structure, and token efficiency in one pass.

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Mastering Write email on Gemini 1.5 Pro