AI Self-Optimization: The "Revised" Ultimate Prompt Formula

In my previous article, Generative AI Hack: The Ultimate Prompt Formula, I explored ways to maximize the potential of AI in generating creative and effective responses. Building on that, I had an interesting idea: why not ask AI how it would improve its own performance? I had a conversation with ChatGPT 4 and Claude 2.1, asking them directly how they would enhance their own efficiency in understanding and responding to prompts. The revised prompt formula uses fewer tokens and produces similar output. I asked each language model the same question: "How can I improve the following prompt to provide the most efficient parameters to produce the desired output with the least number of tokens?" Check out the responses below.

Original Prompt Formula

As a [role|persona], 
I want to [action], 
so that [benefit|goal], 
in [list, paragraph, JSON, CSV, HTML, Markdown] format, 
with a [character|word length] limit, 
written in a [casual, formal, professional, friendly, informative] tone, 
and [academic, journalistic, creative, technical] style, 
while considering the following: [context, examples, constraints, user preferences, integration points, success criteria].        

ChatGPT 4

To optimize the efficiency of your prompt while maintaining clarity and specificity, you can restructure it to minimize redundancy and focus on the most critical elements.

As a [role], I need a [format: list/paragraph/JSON/CSV/HTML/Markdown] output of [action], capped at [character/word limit], in a [tone: casual/formal/professional/friendly/informative] and [style: academic/journalistic/creative/technical], addressing [context/examples/constraints/preferences/integration/success criteria].        

Key Changes

1. Condensed Format: Combines similar elements (like format and length) to reduce repetition.
2. Clear Hierarchy: Prioritizes the role, action, and output format, as these are typically the most crucial elements.
3. Flexible Placeholders: Uses brackets to indicate variable parts, ensuring easy customization without altering the prompt's structure.
4. Comprehensive Yet Compact: Covers all necessary aspects (context, constraints, etc.) in a single, streamlined sentence.

This revised prompt should guide the LLM to understand your needs efficiently, without unnecessary verbosity.

Example Prompt

As a marketing manager, I need a list output of potential digital marketing strategies, capped at 500 words, in a professional and informative tone, addressing current market trends, budget constraints, and preferences for social media integration and measurable success criteria.        

• Role: Marketing Manager
• Action: Identifying potential digital marketing strategies
• Output Format: List
• Length Limit: 500 words
• Tone: Professional and informative
• Style: Not explicitly mentioned, but implied to be business-oriented
• Additional Considerations: Addressing market trends, budget limits, social media integration, and measurable success metrics

Example Prompt Response

As a marketing manager, to effectively plan your digital marketing strategies within the context of current market trends, budget constraints, and a focus on social media integration and measurable success criteria, here is a list of potential strategies:

1. Content Marketing: Develop engaging, SEO-optimized content tailored to your target audience. Focus on creating blog posts, videos, infographics, and podcasts that provide value and encourage sharing on social media platforms.
2. Social Media Marketing: Leverage popular social media channels like Facebook, Instagram, LinkedIn, and Twitter. Tailor content to each platform, engage with your audience, and use analytics tools to measure engagement and reach.[The list included a total of 14 results]

Each of these strategies should be tailored to fit within your budget constraints and should include mechanisms for tracking and measuring success, particularly in terms of social media engagement and conversion rates.

Claude 2.1

Here is one way to make the prompt more efficient while still conveying the key parameters:

[Role] seeking [action] to achieve [goal/benefit] as [format] with [length] limit, [tone], and [style], considering [context].        

Key Changes

I removed some of the unnecessary verbosity to make the prompt more concise. Using square brackets allows specifying the key details without additional words. This focuses on the most important details in a compact way while still allowing flexibility to describe the desired output.

Example Prompt

Teacher seeking summarize key concepts from lecture to reinforce student learning as bullet points with 100 word limit, casual tone, and informative style, considering intro biology course for non-majors.        

• Role: Teacher
• Action: Summarize key concepts from lecture to reinforce student learning
• Output Format: Bullet points
• Length Limit: 100 word limit
• Tone: Casual
• Style: Informative
• Additional Considerations: Intro biology course for non-majors

Example Prompt Response

Here is a 125 word summary of key concepts from an intro biology lecture for non-majors in casual tone and informative style:

• Cells are the basic units of life. They come in different shapes like spheres or rods based on their function.
• DNA carries the instructions for life processes in a code made up of 4 chemicals called bases. The sequence of bases determines specific traits.[The list included a total of 5 results]

I aimed to cover fundamental biology concepts at an intro level in easy to grasp bullet points for non-experts.

Conclusion

I personally like Claude's revised prompt formula the best:

[Role] seeking [action] to achieve [goal/benefit] as [format] with [length] limit, [tone], and [style], considering [context].        

This experiment to enhance the efficiency of language model prompts through AI's own insights has produced great results. By directly engaging with ChatGPT and Claude, I found a more streamlined and effective approach to crafting prompts. The revised formula not only conserves tokens but also retains, if not enhances, the quality of the output. This demonstrates the remarkable (and scary) capabilities of AI in self-improvement and optimization, with AI as an effective and active participant in its own evolution. So I guess we can use AI to improve AI.