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Updating wording
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examples/gpt-5/gpt-5_troubleshooting_guide.ipynb

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"\n",
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"## General troubleshooting \n",
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"Many of the above prompt additions were generated through metaprompting. It’s possible to ask GPT-5 at the end of a turn that didn’t perform up to expectations how to improve its own instructions. The following prompt was used to produce some of the solutions above, and can be tuned to meet your particular needs.\n",
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"Many of the above prompt additions were generated through meta prompting. It’s possible to ask GPT-5 at the end of a turn that didn’t perform up to expectations how to improve its own instructions. The following prompt was used to produce some of the solutions to overthinking problems above, and can be modified to meet your particular needs.\n",
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"```\n",
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"That was a high quality response, thanks! it seemed like it took you a while to finish responding though. Is there a way to clarify your instructions so you can get to a response as good as this faster next time? It's extremely important to be efficient when providing these responses or users won't get the most out of them in time. Let's see if we can improve!\n",
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"That was a high quality response, thanks! It seemed like it took you a while to finish responding though. Is there a way to clarify your instructions so you can get to a response as good as this faster next time? It's extremely important to be efficient when providing these responses or users won't get the most out of them in time. Let's see if we can improve!\n",
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"1) think through the response you gave above\n",
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"2) read through your instructions starting from \"<insert the first line of the system prompt here>\" and look for anything that might have made you take longer to formulate a high quality response than you needed\n",
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"3) write out targeted (but generalized) additions/changes/deletions to your instructions to make a request like this one faster next time with the same level of quality\n",
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"```\n",
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"When metaprompting inside of this context, it is important to generate responses a few times if possible and examine elements of its response that are common between them. Some improvements or changes it proposes might be overly specific to that particular situation, but you can often simplify them to be more general."
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"When meta prompting inside of a specific context, it is important to generate responses a few times if possible and pay attention to elements of its responses that are common between them. Some improvements or changes the model proposes might be overly specific to that particular situation, but you can often simplify them to arrive at a general improvement. We recommended that you create an eval to measure whether a particular prompt change is better or worse for your particular use case."
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