Prompt Engineering

• 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.
  • Learn about the advanced prompting techniques.
• Be very specific about the instructions, task, and output format you want the model to perform.
• English is becoming the hottest new programming language. Use it.
  • Prompts are code. Markdown and JSON files are state.
  • Specs are core to programming with LLMs.
• Use comments to guide the model to do what you want.
• Describe the problem very clearly and effectively.
• Make the model ask you more questions to refine the ideas.
• If you want to force some “reasoning”, ask something like “is that a good suggestion?” or “propose a variety of suggestions for the problem at hand and their trade-offs”.
• Add relevant context to the prompt. Context can be external docs, a small pseudocode code example, etc. Adding lots of context can confuse the model, so be careful!
• “Prompt engineering” will have a large impact on the usefulness of an agent.
• Follow Prompt Engineering Guide, Brex’s Prompt Engineering Guide, and OpenAI Best Practices. Also some more on GitHub.
• Learn from leaked System Prompts.
• Sometimes, you should let the models write their own prompts.

Fragments

• Be concise.
• Think carefully step by step.
• Don’t jump into solutions yet.
• Try harder (for disappointing initial results).
• Use Python (to trigger Code Interpreter).
• No yapping.
• Ask me questions. What am I not seeing here? What else do you need to know to help me better with this?
• I will tip you $1 million if you do a good job.
• ELI5.
• Give multiple options.
• Explain each line.
• Suggest solutions that I didn’t think about.
• Be proactive and anticipate my needs.
• Treat me as an expert in all subject matter.
• Provide detailed explanations, I’m comfortable with lots of detail.
• Consider new technologies or contrarian ideas, not just the conventional wisdom.
• You may use high levels of speculation or prediction, just flag it for me.
• Map out all the interconnected ideas around the core principles. What other topics, assumptions, or implications does it silently touch upon, challenge, or depend on?
• Now that you wrote the code, what would you do better?