Prompt engineering guide

Writing effective prompts is the core skill of AI mastery. These five principles will transform your results.

1

Clarity and specificity

The clearer and more specific your prompt, the better the output. Vague requests produce vague results.

  • ›State what you want upfront
  • ›Specify the format of the output
  • ›Include edge cases you care about
  • ›Use active voice and direct language
2

Providing context

Context transforms outputs. Give the AI the information it needs to understand your situation fully.

  • ›Describe your background or expertise level
  • ›Explain what you will do with the output
  • ›Share relevant constraints or requirements
  • ›Describe the audience or purpose
3

Using examples

Examples are one of the most powerful tools in prompt engineering. Show, do not just tell.

  • ›Provide 1-3 concrete examples of what you want
  • ›Show both successful and unsuccessful examples to clarify boundaries
  • ›Label your examples clearly
  • ›Use examples matching your exact use case
4

Iterative refinement

The first output is rarely perfect. Treat AI as a conversation, not a one-shot interaction.

  • ›Request specific changes rather than starting over
  • ›Build on what works; discard what does not
  • ›Test variations on the prompt itself
  • ›Track what prompts produce your best outputs
5

Format specification

Be explicit about how you want information structured. Structure enables downstream use.

  • ›Request markdown, JSON, CSV, or plain text as needed
  • ›Specify heading levels and hierarchy
  • ›Ask for bulleted lists, tables, or prose as appropriate
  • ›Define any custom notation or structure you need

Quick examples

Weak prompt

Write me something about productivity

Strong prompt

Write a 500-word guide for software engineers on maintaining deep focus during code reviews. Use markdown headings. Include three concrete techniques with practical examples. Assume the reader works in a collaborative environment with frequent interruptions.

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