How to understand how a LLM arrived at its response

This prompt is useful for dissecting an AI's response to a given prompt, particularly focusing on large language models (LLMs), by identifying the steps and reasoning processes the AI likely followed. It helps users understand how LLM AI functions, shedding light on the logical flow, decision points, and assumptions that underlie the AI's conclusions. By understanding how LLM AI works, users can gain insights into the operation and decision-making processes of large language models.

What content you'll need to provide

You will need the original prompt given to the AI and the AI's response to that prompt. To analyze how LLM AI works, break down the reasoning process step by step, noting key decision points, assumptions, and logical connections. Consider the main components or arguments in the response, infer any background knowledge or context the AI might have used, and highlight any logical leaps or assumptions made. Pay special attention to specific techniques or approaches the AI employed, such as problem breakdowns, analogies, or the application of specific knowledge typical of large language models. Present the reasoning process in a clear, step-by-step format and provide a summary of the AI's approach, offering key insights about the reasoning process of LLM AI.

Here's the prompt

You are tasked with analyzing an AI's response to a given prompt and showing the chain of thought that led to that response. This analysis will help users understand how the AI arrived at its conclusion and the reasoning process behind it.

Here is the original prompt given to the AI:

<prompt>
[insert prompt]
</prompt>

And here is the AI's response to that prompt:

<response>
[insert response]
</response>

Your task is to analyze this response and show the chain of thought that the AI likely followed to arrive at this response. Break down the reasoning process step by step, identifying key decision points, assumptions, and logical connections.

Present your analysis in the following format:

<chain_of_thought>

[First step in the reasoning process]
[Second step in the reasoning process]
[Third step in the reasoning process]

...

n. [Final step leading to the conclusion]

</chain_of_thought>

When conducting your analysis, consider the following:

Identify the main components or arguments in the response
Infer any background knowledge or context the AI might have used
Highlight any logical leaps or assumptions made
Note any specific techniques or approaches the AI seems to have employed (e.g., breaking down the problem, using analogies, applying specific knowledge)

After presenting the chain of thought, provide a brief summary of the AI's approach and any key insights about its reasoning process. Present this summary in the following format:

[Your summary of the AI's approach and key insights]

</summary>

Remember, the goal is to provide a clear and insightful explanation of how the AI likely arrived at its response, helping users better understand the AI's reasoning process.

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Getting the answer you need from SmartChat™ often means going deeper into the content after your first prompt above, which you can accomplish by:
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- Asking followup questions (we'll provide you with some suggested followup prompts)

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Understand how a LLM arrived at its response

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What content you'll need to provide

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