How to Make AI Content That Actually Sounds Like You
Generic AI sounds like generic AI. Here's how to train and prompt AI on your voice, knowledge base, and past posts so the output is unmistakably yours.

The complaint about AI content is always the same: it sounds like AI. And usually, it's true, because most people give the model nothing but a blank prompt and a topic.
Slop is an inputs problem
A model with no context defaults to the average of the internet. To get your voice, you have to feed it your signal.
The three inputs that fix it
- Voice, your past posts, so phrasing and rhythm match how you write.
- Knowledge, your docs, talks, and transcripts, so the substance is real.
- Point of view, your brand strategy, so the takes are actually yours.
Think of AI as an editor who has read everything you've ever published, not a ghostwriter inventing opinions for you.
Scale your voice, don't replace it
Used well, AI removes the blank-page tax and the formatting grind. What stays human is the part that matters: your judgment, your stories, and your point of view.
Frequently asked questions
Will readers be able to tell it's AI-assisted?+
Not if it's grounded in your real expertise and trained on your voice. The goal is to scale how you already sound, not to fabricate a new persona.
What inputs matter most?+
Your past posts (voice), your knowledge base (substance), and your brand strategy (point of view). With those three, output stops sounding generic.
Building CaptureFlow so founders can turn their expertise into content without a team. Writes about founder-led content, AI, and distribution.
Founder · 10+ years building products and audiences
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