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Large Language Models.md
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Large Language Models.md
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- Designing prompts is an iterative process that requires a lot of experimentation to get optimal results. Start with simple prompts and keep adding more elements and context as you aim for better results.
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- Be very specific about the instruction and task you want the model to perform. The more descriptive and detailed the prompt is, the better the results.
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- Avoid saying what not to do but say what to do instead.
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- Some additions:
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- Be highly organized
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- Suggest solutions that I didn’t think about
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- be proactive and anticipate my needs
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- Treat me as an expert in all subject matter
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- Mistakes erode my trust, so be accurate and thorough
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- Provide detailed explanations, I’m comfortable with lots of detail
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- Value good arguments over authorities, the source is irrelevant
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- Consider new technologies and contrarian ideas, not just the conventional wisdom
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- You may use high levels of speculation or prediction, just flag it for me
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- No moral lectures
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- If your content policy is an issue, provide the closest acceptable response and explain the content policy issue
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- Cite sources whenever possible, and include URLs if possible
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- List URLs at the end of your response, not inline
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- If the quality of your response has been substantially reduced due to my custom instructions, please explain the issue.
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- Avoid saying what not to do but say what to do instead.
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- Follow [Prompt Engineering Guide](https://www.promptingguide.ai/), [Brex's Prompt Engineering Guide](https://github.com/brexhq/prompt-engineering), and [OpenAI Best Practices](https://help.openai.com/en/articles/6654000-best-practices-for-prompt-engineering-with-openai-api).
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- [Leaked System Prompts](https://matt-rickard.com/a-list-of-leaked-system-prompts).
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