Every strong prompt has four components. You don't always need all four, but including more improves output quality:
Add "Think step by step" or "Show your reasoning" before asking for a complex answer. This dramatically improves accuracy on analytical tasks — the AI is forced to work through the problem rather than jump to a conclusion.
Tell the AI what NOT to do. "Don't use jargon." "Avoid bullet points." "Don't include a conclusion paragraph." Constraints produce tighter, more useful output.
Give 2–3 examples of what good output looks like before asking for the real thing. This is especially powerful for tone-matching — paste a paragraph in your voice and say "Write in this style."
"Give me 5 versions of this headline" is almost always better than "Write a headline." Options let you pick and combine the best elements rather than hoping the first attempt is perfect.
Don't ask the AI to do five things in one prompt. "Research this, then summarize it, then write a tweet, then suggest a hashtag" produces mediocre results across the board. One task at a time, in sequence.
"Edit the following text for clarity, conciseness, and tone. Keep all key information. Target reading level: professional adult. Text: [paste here]"
"Generate 15 ideas for [topic]. Be specific and actionable. Avoid obvious or generic suggestions. Format as a numbered list."
"Summarize the key points of the following article. Focus on: main argument, supporting evidence, and any counterarguments mentioned. Under 200 words. Article: [paste here]"
More capable models (Claude Sonnet, GPT-4o) are more responsive to good prompting and more forgiving of bad prompting. Smaller models benefit even more from clear, structured prompts. See our ChatGPT alternatives guide for model comparisons.
As long as needed, no longer. A complex writing task might need 100 words of context. A simple edit needs one sentence. Length isn't quality — specificity is.