Your AI Content Might Be Fine. Maybe That's The Problem.
If you use AI to help write anything, whatever your niche is, you've probably had this moment: the draft looks fine, technically correct, nice sentences, but something about it feels a little off. Maybe a little too polished, a little too generic, but you can tell - or maybe just sense - that it's written by an AI bot.
I ran into this when setting up my voice.md file, so I built something to fix it. The guide I created doesn't just describe the tone I want, it defines it with real examples.
Here's the structure that actually worked:
  1. Gold standard examples: 2 to 3 pieces of writing that are exactly the tone I'm going for, used as a reference before writing anything new. Each example is followed by a "Why it's good" explanation.
2. Bad examples with annotations: writing that looks fine on the surface but fails in a specific, named way.
3. A drift patterns table: short phrases that sound right but aren't, next to the actual reason they don't work.
4. Mechanical rules: specific, almost boring rules that are easy to forget but change everything once you write them down
The biggest shift for me was realizing tone can't just be described, it has to be demonstrated.
Telling an AI to "sound warm" or "sound authentic" doesn't work nearly as well (or at all) as showing one good example and one bad example side by side, then naming exactly what's different between them. More examples = better output. Explaining the failures is huge.
If you're using AI for anything where tone actually matters, I'd genuinely recommend creating something like this before you let it write your first real piece. It saved me a ton of revision time and kept my content sounding like an actual person instead of a generic AI draft.
Happy to answer questions if anyone wants to build their own version of this.
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Carla Bosteder
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Your AI Content Might Be Fine. Maybe That's The Problem.
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