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AI that writes LinkedIn posts in your voice

The complaint about AI-written LinkedIn content is almost always the same: it sounds like AI. The posts are competent and completely generic, full of tidy parallel sentences and the same handful of influencer cadences, and anyone who knows you can tell you did not write them. The cause is structural. The typical tool starts from a text prompt and has nothing to anchor the voice, so it defaults to the average of every LinkedIn post ever scraped. Edgar anchors on two things instead. First, your imported LinkedIn posts, which give the model your actual vocabulary, sentence length, and rhythm. Second, a weekly conversation that supplies real specifics from your week rather than a generic prompt. The drafts come out of those two inputs, which is why they read closer to you than to a LinkedIn influencer template, and why the match gets tighter as the system sees more of your sessions.

Short answer

An AI that learns your voice from your imported posts and a weekly conversation, then drafts LinkedIn content that reads like you rather than a generic influencer.

Founders and operators who like the idea of AI-written LinkedIn posts but have been put off by how obviously generic the output usually sounds.

How it works

  1. 1You import your existing LinkedIn posts when you set up. These become the voice reference the model writes against.
  2. 2Once a week you have a 10 to 15 minute conversation with the AI agent about what actually happened: customers, decisions, opinions, surprises.
  3. 3A long pipeline drafts 3 to 6 posts, matching your phrasing and rhythm from the imported posts and built around the specifics from the call.
  4. 4You review each draft, edit anything that's slightly off, or refine it with a chat instruction until the voice is right.
  5. 5Approved posts publish to LinkedIn on your schedule.

Why voice, not text

  • +Imported posts give the model a real voice to match, so it isn't defaulting to the scraped average of LinkedIn.
  • +A conversation supplies the specific stories that make a post sound like a person. A text prompt usually can't.
  • +The voice match improves session over session as the system sees more of how you actually write and what you approve.
  • +You stay in control of the final wording. Anything that drifts gets edited or refined before it publishes, so nothing goes out that doesn't sound like you.

Example post

Tried four AI tools for LinkedIn last year. Every draft read like the same vaguely confident stranger wrote it. The thing that fixed it was feeding in my old posts as the reference and talking through real specifics instead of typing a prompt. My co-founder read last week's drafts and couldn't tell which one I'd edited and which were untouched.

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