AI didn’t kill your LinkedIn reach. Pasting Claude’s first draft did.
I run most of my business on Claude and n8n. Research, outlines, transcript cleanup, CRM enrichment, lead scoring, meeting prep — the model touches almost everything. But it doesn’t touch the words you actually read from me. Not on LinkedIn, not in emails, not in reels.
Here’s why, and here’s the exact system I use so you can steal it.
The tell everyone is missing
Every AI-drafted LinkedIn post has the same fingerprints:
- Opens with a rhetorical question or a soft setup line
- Uses the phrase "here are X lessons" or "here’s what I learned"
- Bullet points with parallel structure that’s too clean
- A closing line like "What’s your take?" or "Which one resonates?"
- Zero specific numbers, names, or scars
Your buyer reads 30 of these a day. So does the algorithm. The moment your post pattern-matches to the other 29, distribution collapses and human attention slides right past.
This isn’t about "AI writing bad." Claude can write beautiful prose. The problem is that generic writing gets generic reach, and a first draft from any LLM is generic by definition — it’s the statistical average of the internet.
The line I draw
Simple rule: AI does the thinking work I can verify. Humans do the choosing work only I can do.
What that means in practice:
- AI does the research. Pull sources, summarize threads, find counterexamples, compare frameworks.
- AI does the outlines. Give me five angles on this topic, ranked by contrarian potential.
- AI runs the pipelines. Transcription, tagging, scheduling, repurposing snippets.
- The human writes the hook. Because the hook is a taste decision, not a probability distribution.
- The human tells the story. Because only you were in the room.
- The human picks the fight. Because opinions require skin, not tokens.
My actual pre-post workflow
Here’s what happens before I post anything on LinkedIn. It takes me around [X] minutes per post.
1. Voice memo the raw idea (2 min)
I record a voice note the second I have a thought worth posting. Usually triggered by a client call, a mistake I made, or something I disagree with. Raw, unstructured, my actual words.
2. Transcribe and structure with Claude (3 min)
I run the transcript through Claude with a prompt like: "Here’s a voice memo. Pull out the single sharpest claim. List every specific detail I mentioned. Do not rewrite anything in your own voice."
Notice what I’m asking for: extraction, not generation. Claude is a highlighter, not a pen.
3. Write the hook myself
I open a blank doc and write the first two lines from scratch. This is non-negotiable. The hook is 80% of whether the post works, and it’s the one part that has to sound like a person who has been through something.
Bad AI hook: "Most founders don’t realize this about AI content…"
Human hook: "AI didn’t kill your LinkedIn reach. Pasting Claude’s first draft did."
Same topic. One reads like a template. The other reads like a person picking a fight.
4. Draft the body in my own words
I write the body using the details Claude extracted. I keep specific numbers, real names, actual timelines. If I don’t know a number, I leave a bracket, not a fake stat.
5. Use Claude as an editor, not a writer
Final pass, I paste my draft in and ask: "What’s soft here? Where am I hedging? Which sentence sounds like every other LinkedIn post?"
Claude is excellent at critique. It’s mediocre at replacement. So I take the critique and rewrite those lines myself.
Why this actually works for reach
LinkedIn’s algorithm isn’t (only) hunting for AI text. It’s hunting for dwell time and meaningful reactions. Both drop when a post reads generic, because readers pattern-match and scroll.
Specificity is what stops the scroll. Specificity is what prompts a DM. And specificity is exactly what a first-draft LLM strips out, because averages don’t have specifics.
When I paste a Claude draft, I get [low number] impressions and zero DMs. When I write it myself and use Claude as an intern behind the scenes, I get [higher number] impressions and [X] DMs — and one of those DMs is worth more than the whole month of "5 lessons I learned" posts combined.
The one prompt swap that fixes 80% of it
Stop asking Claude: "Write me a LinkedIn post about X."
Start asking Claude: "I’m writing a LinkedIn post about X. Here are my notes. Ask me 10 questions that would make this post more specific before I draft it."
Now Claude is doing what a good editor does: pulling the story out of you. You still write the post. You just write a much better one.
The honest test
Read your last five posts out loud. If they sound like something you’d say to a friend at a bar, you’re writing. If they sound like a keynote nobody asked for, the model is writing them for you.
Use AI as your research intern. Not your ghostwriter. Your buyer can tell the difference — and so can the algorithm.