Writing Insights
What actually works on LinkedIn, read off real posts.
Operator notes from running a roster of voices. No engagement-bait listicles, no growth-hacking gospel (we do neither). Every note here was read off real published posts, and the receipts are on this page: the numbers, and the links to check them.
- Real voices
- 5
- Impressions, counted
- 76,505
- Posts dissected below
- 9
- Em dashes in them
- 0
- Mechanics1
- Openers1
- Employee content1
- Analytics1
- Specificity1
- Distribution1
- Cadence1
The full index
7 field notes- The cold open beats the hook.Hooks announce themselves. Cold opens just start. One of them gets read past line one.
- Many voices, one team: writing for a whole team at scale without the blend.A whole roster of employees, one team, zero blended-into-mush posts. The system that keeps each voice its own.
- The metric that actually explains what lands.Likes are a lagging vanity number. The leading signal is velocity: how fast a post catches in its first hour.
- Specific beats clever, every time.The abstract insight scrolls past. The oddly specific detail stops the thumb. Why the number you almost cut is the post.
- The first comment is yours to lose.You hit post and walked away. The hour you skipped is the hour that decides reach. What the accounts that travel do in the first sixty minutes.
- Consistency is a format problem, not a willpower one.You don't fall off because you lack discipline. You fall off because every post starts from a blank page. Fix the page, not the person.
Read from real posts
These notes are not theory. They came off real posts.
Nine posts Michael Maximoff actually published, Chief Growth Officer, Co-Founder @ Belkins. Every figure is real and every date links to the live LinkedIn post, so you can check any row. This is the raw material the notes above were read from.
- 220words, median post
- 6 of 9/9open in first person
- 2–15blank-line beats
- 0em dashes, counted
| Shipped | First line, his words | Words | Beats | ER* | Views |
|---|---|---|---|---|---|
| Apr 4, 2026 | My co-founder is obsessed with AI. Can anyone relate? | 220 | 12 | 0.5% | 12,187 |
| Apr 13, 2026 | I was driving, and after the first 20 minutes, I said to myself, “What an incredibly insightful conversation, was I really part of it?” | 188 | 9 | 0.5% | 8,374 |
| May 4, 2026 | We grew the BLKNS community to 3,600 members. Then we stopped investing. Why? | 338 | 15 | 0.9% | 7,454 |
| Mar 9, 2026 | I'm watching Apollo, Outreach, SalesLoft, Nooks, Instantly and many others all converge into the same tool. | 249 | 13 | 1.5% | 3,861 |
| Apr 2, 2026 | Just wrapped up an interview with marketing GOAT Udi Ledergor, ex-CMO and Chief Evengelist at Gong. Excited to share this one soon 💣 | 47 | 2 | 4.3% | 2,914 |
| Feb 24, 2026 | You shouldn't have to pay to learn. | 144 | 9 | 4.4% | 2,523 |
| May 6, 2026 | Upd from Belkins: we’re steadily trying to figure out Lead Gen 3.0. | 296 | 15 | 4.2% | 2,115 |
| May 3, 2026 | Abbas Somji, thank you for inviting me onto your podcast. It’s refreshing to be on the other side of the interview for a change. | 63 | 3 | 3.6% | 2,095 |
| Apr 9, 2026 | I bet 90% of tech leaders spend at least 1–2 hours a day working on AI. People reading this fall into this group. | 239 | 10 | 3.9% | 2,012 |
| 9 posts · totals | 1.6% | 43,535 | |||
Words and beats read on wider screens*Engagement rate, derived: (reactions + comments + shares) / views. These 9 are the publicly quoted subset of Michael’s 31 tracked posts.
The rules we read by
The same rules are wired into the engine.
These notes are not content marketing. They are how the writing engine actually thinks. Below are its real system-prompt rules, quoted word for word, each one behind a note above.
“Compress quickly. Get to the point with very little runway.”backs · The cold open beats the hook“Posts should end 20-35% earlier than feels comfortable.”backs · Ended four lines too late“Use contrast well. The market does something. The client does the opposite.”backs · Specific beats clever“Never use: The em dash symbol (AI tell).”backs · 0 em dashes, counted below“Fabricated specifics are the single biggest failure mode of AI-written posts.”backs · Never invent a number
The Writing Assistant applies every one of them, in each profile’s own voice. The advice and the product are the same thing.
Reading about it is step one. Writing it is the engine.
Put a profile in and the assistant drafts in their voice, with every rule above already running. The trial is the whole platform, not a demo.
7-day full-access trial. $0.95 to start. Cancel anytime.