Fix a Vague Prompt
'Make it good', 'be detailed', 'keep it interesting' — vague prompts get vague output. The fix is mechanical: replace every fuzzy word with a checkable instruction.
View Resource →Rewrite a weak prompt into a stronger one — vague wording fixed, gaps filled, goal unchanged.
'Make it good', 'be detailed', 'keep it interesting' — vague prompts get vague output. The fix is mechanical: replace every fuzzy word with a checkable instruction.
View Resource →The fastest fix for mediocre AI output is rewriting the prompt: vague words become concrete instructions, hedges become commitments, and missing elements get filled.
View Resource →Format, length, and exclusions are the three levers that make AI output land in usable shape. A rewrite shows how to retrofit them onto a prompt that has none.
View Resource →If you can't say what makes the output right, the model can't either. Success criteria turn 'make it good' into a checkable definition of done.
View Resource →Generic prompts produce generic output. Specificity is added in slots — audience, context, named requirements — and a rewrite shows exactly which slots yours is missing.
View Resource →The full enhancement pass in one worked example: fix vague wording, commit the hedges, strip filler, fill the gaps — without changing what the prompt asks for.
View Resource →'Write a blog post about X, make it engaging' is the most rewritten prompt on the internet. Here's its strong form — angle, reader, hook rule, and length.
View Resource →Marketing prompts built from 'compelling' and 'persuasive' produce copy that sounds like everyone's. The rewrite swaps adjectives for an offer, a reader, and one CTA.
View Resource →'Research X and tell me what you find' returns a topic summary, not an answer. The rewrite adds the control a research ask needs: scope, criteria, and output shape.
View Resource →'Be nice and fix their issue' is a liability in a support prompt. The rewrite adds the control lines support actually needs: boundaries, length, and a next step.
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