Most people prompt AI once and hope for the best. The real skill is knowing when to refine versus when to scrap everything and start over.
The story
After thirty years writing code and eight years deep in AI, I’ve noticed something: most people treat prompting like they’re filing a support ticket. Write it once, hope for the best, maybe tweak a word or two if it fails.
That’s not how this works.
The real skill isn’t writing the perfect prompt on the first try. It’s knowing when to keep refining and when to throw it out and start fresh.
I iterate when the output is close. When I can see the AI understood most of what I wanted but missed on tone, or got the structure right but the details wrong. That’s when I add constraints, clarify instructions, test again. Small adjustments compound. I’ve taken prompts from 60% useful to 95% through careful iteration – adjusting context, tightening format requirements, being more specific about what I actually need.
But iteration has limits.
When I’ve refined three or four times and the output is still fundamentally off-target, I stop. Over-refining creates diminishing returns. The prompt becomes a mess of add-ons and corrections that confuse more than clarify.
That’s when I start over.
Starting fresh means rethinking the problem. Maybe my initial framing was too vague. Maybe I’m asking one prompt to do the work of three. Maybe I need to break it into smaller pieces or completely restructure how I’m approaching the task.
The pattern I’ve seen: people who make the most of AI aren’t the ones who write clever prompts. They’re the ones who recognize when they’re on the right path versus when they need to reset.
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