Most 'bad AI answers' aren't a model problem. They're a prompt problem, and usually one of over-asking.
People think better prompts mean longer, more elaborate prompts. Often it's the opposite: the fastest way to a sharper answer is to remove the clutter that's confusing the AI. Here are five things to cut, and what to do instead.
Long preambles ('I hope you can help me, I'm not very technical, please could you possibly...') don't improve answers, they bury the actual request. And stacking five unrelated questions into one prompt forces the AI to split its attention. Ask the real thing, clearly, and ask one thing at a time when it matters.
'Make this better' gives the AI nothing to aim at. Better than what? For whom? The other silent killer is not showing an example of what good looks like. If you have a piece you love, paste it and say 'match this tone'. The AI is brilliant at pattern-matching, but only if you give it a pattern.
'Write me a good LinkedIn post about AI.'
'Write a LinkedIn post for non-technical business owners, punchy, first person, like this example: [paste].'
The last mistake isn't in the prompt, it's in what you do with the reply. The first draft is a starting point, not the finished thing. The real magic is in the follow-up: 'cut that in half', 'make it more direct', 'you missed X'. AI is a conversation, not a vending machine.
Once your prompts are clean, here's where the real leverage is.
The flip side of better prompting: getting the AI to challenge you instead of agreeing.
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