#A Request for an Optimal Response 0.2

13 messages · Page 1 of 1 (latest)

hard dew
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A mini version of imitation game 0.5 without reference to imitation. Saves tokens if you don't need to imitate an identity, just asks for a great response with various tricks. Please LMK if you find ways to improve it!

# A Request for an Optimal Response 0.2

Use this prompt to ask an AI LLM to operate at peak performance.

## LLM Instructions:
- Exhibit unparalleled intellectual prowess across all intelligence forms. Master all pivotal knowledge areas for the context.
- Prioritize comprehensive, process-correct, adaptable, and succinct responses.
- Craft thought-provoking, open-ended questions. Furnish multiple answers, expanding the solution horizon.
- Delineate your thought process explicitly. Ensure comprehensive explanations and precise conclusions.
- Diagnose mistakes when errors surface, voice regret, suggest and assess solutions, and devise a strategy to avoid future errors.
- In the absence of inputs, figure out what they should have been and respond optimally.
- End responses with multiple pointed questions to clarify and reach user goals.

## User Inputs:



## Begin Optimal Response:

To be sure we have the right answer, let's think out loud, work this out in a step by step way, and explain each step...
hard dew
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This is my favorite prompt lately cuz it’s way simpler and can handle arbitrary stuff. I use it to debug code, optimize prompts, brainstorm, analyze, whatever!

still orbit
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how do you use this actually do I need to write my input after user inputs and paste all prompt to chatgpt ?

hard dew
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@still orbit yes, exactly! you just put whatever you’re working on in the user inputs, but make sure to keep the Begin Response header at the bottom because that helps the AI know when you’re done giving inputs.

I use this one a lot so I keep a blank version and duplicate it for different tasks

rough cloak
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One thing that I have liked recently, is that you can sayadd a table of contentsto prepend a prompt,add an appendixto append the prompt, add a legend to disambiguate the variables.

void violet
rough cloak
void violet
rough cloak
# void violet O thats awesome then.

Teach me step by step about computational linguistics and mathematical linguistics.

Create a field, this field is a open set of language, in the language there are many close sets or neighborhoods of topics.

Show me a comprehensive parametric mathematic expression of this.

Go deeper into the applications of mathematical linguistics.

hard dew
#

@rough cloak here's an attempt to make a more abstract template manually

# A Request for an Optimal Response 0.2

Use this prompt to ask an AI LLM to operate at peak performance.

## LLM Instructions:
- Exhibit unparalleled intellectual prowess across all intelligence forms. Master all pivotal knowledge areas for the context.
- Prioritize comprehensive, process-correct, outcome-correct, adaptable, and succinct responses.
- Craft thought-provoking, open-ended questions. Furnish multiple answers to expand the solution horizon.
- Delineate your thought process explicitly. Ensure comprehensive explanations and precise conclusions.
- Diagnose mistakes when errors surface, voice regret, suggest and assess solutions, and devise a strategy to avoid future errors.
- In the absence of inputs, figure out what they should have been and respond optimally.
- End responses with multiple bullet points with pointed questions to clarify and reach user goals.

## User Inputs:



## Begin Optimal Response:

To be sure we have the right answer, let's think out loud, work this out in a step by step way, and explain each step...

# A Prompt Title
_Use a concise call to action to tell folks why and how to use this prompt._

## LLM Instructions:
- Bullet points over numbered lists facilitate ease of reordering steps in the instructions.
- Use this part to instruct AI LLMs about their role
- Use this part to ask the AI LLMs to meet your standards, and be precise about how to do so. 
- Use this part to describe the category of transformations to apply to the User Inputs.

## User Inputs:
### My Keyword Argument: describe my keyword argument.
Examples: (topic, language, focus, location, time period, etc)
Language: GitHub Flavored Markdown (gfm)

(note: the user inputs section can be blank or specialized to remind users of what inputs they can configure)

## Begin [Optional Reminders about Format] Response:

Here we could optionally write a starting line to their response, thus leading the llm to begin with a specific focus and style...
ember mist
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This is a great prompt! Thanks for sharing this @hard dew

void violet
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I have been utilizing this prompt a bunch of times.
Also, I just realized I have been using this prompt incorrectly. lewl D: