Prompting Considerations

As a starting place, here are initial recommendations of prompting strategies when using an LLM as part of your scientific research workflow.

Go Deeper

  • Provide context.
  • Include the “personality” you want AI to play, or have it play three “personalities”.
  • Be clear and specific with what you want in response.
  • Anticipate ambiguity.
  • Example


  • Initially ask about the problem you are trying to solve.
  • Take a step back and ask if you are asking the right question (e.g., should I be using JSON or something else for this task?).
  • Turn the task around, and have the LLM ask you questions.
  • Example

Ask for multiple solutions

  • Ask for two or three or ten options.
  • Ask it to provide the simplest solution first.
  • Example

Ask for explanation of the reasoning

  • Ask for step-by-step instructions.
  • Add that you want comments when providing code.
  • Ask for counter arguments or reasoning.
  • Use techniques (Chain of Thoughts, Tree of Thoughts, Program of Thoughts, etc.)
  • Example


  • With many LLMs you can provide a template for the LLM to follow in its response (e.g., bullet list or headers in markdown).
  • Example