- A short prompt is often enough; larger or more important tasks should include only the parts that matter.
- Goal: Describe the result, not detailed steps unless the process itself matters.
- Context: Add only information or sources that could change the result, and explain what the model should take from each. Too much context can confuse the model.
- Output: Name the audience, format, length, and intended use.
- Boundaries: State what must stay unchanged, what to avoid, and what requires approval.
- Designing prompts is an iterative process that requires experimentation.
- Start simple. Review the result and ask for the specific change you want.
- For important work, ask the model to check the result and flag missing information instead of guessing, then review it yourself.
- Learn about the advanced prompting techniques.
- English is becoming the hottest new programming language. Use it.
- 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”.
- “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.
- 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?