The seven silent mistakes that sabotage your AI output every day — and the precise fixes that reverse each one immediately.
3 min read
Just now
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You’ve spent five days building your prompting foundation. You know the five components. You understand role prompting. You’ve started your template library. You’re writing better prompts than 95% of AI users on the planet.
But even with all of that, there are seven specific mistakes that creep into prompts silently — invisible until you see the output and wonder why it missed the mark. They’re not obvious errors. They’re structural gaps that look fine from the outside but hollow out the result.
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Today, we name all seven. We show exactly what each one looks like in the wild. And we give you the surgical fix for every single one.
The Quick Diagnostic Checklist
Before you send any important prompt, run it against this checklist. Seven questions. Thirty seconds. The difference between output you can use and output you have to rewrite.
One real prompt — before and after all seven fixes
To see the full transformation in one place, here’s the same email request written with zero fixes, then rewritten after applying all seven diagnostics. Read both out loud. The difference is not subtle.
Tomorrow, on Day 7, we shift from what can go wrong to something deeply practical: Context Windows — how AI memory actually works, how much information you can give it, and the strategy for feeding AI exactly the right information so it never runs out of context mid-task.
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