LinkedIn Content Strategy for AI Operations Advisors | Netwarm
LinkedIn playbook · Case study
LinkedIn content strategy for AI operations advisors: how a Washington, DC operator and author reached 200 founders and executives in one month
We read every reaction on 30 posts from a Washington, DC AI operations advisor and author. 1,186 people, 200 founders and executives. Here is what brings buyers, what brings peers, and the 5 posts we'd publish next.
Max Sawyer · Netwarm··11 min read
The creator in this case studyA Washington, DC AI operations advisor and author
Followers45,590
PostsDaily, ~7 a week
Sells
These numbers are from 6 November. Your audience has already moved.
New founders and executives turn Hot every week and others go quiet. Run your free scan to see today’s version, with the names.
AI transformation advisory for companies (CRM replacement, quoting systems, AI-fluent teams), flat-rate application builds, a paid newsletter and keynotes
PeriodOct 8 – Nov 6
Ideal client: founders, owners and operators of small and mid-sized companies who want AI to change how the business runs, not just add another tool.The challenge: The advisor posts every day, from Anthropic's S-1 to Gary's spreadsheet. The posts travel well: one passed 440 reactions. But AI creators, coaches and consultants read along too. Which posts reach the owners and executives who'd hire an operator?
Key takeaways
1 in 6 readers is a founder or executive.200 founders, owners, CEOs, VPs and directors reacted in one month: 16.9% of the 1,186 people who reacted. Peers were twice as many: 400.
Money and big-tech breakdowns lead.Posts on the AI economy brought 18.5% founders and executives, build-in-public posts 12.2%. The Anthropic S-1 post reached 26.8%, the highest share.
15 founders and executives are Hot right now.They reacted to 5 posts or more. One of them reacted to 19 of the 30.
01
Who actually reads you, and what the LinkedIn algorithm changed
The advisor posts every morning on how AI changes the way companies run: the spreadsheet nobody documented, the approval layers, the money behind the AI boom, and why we are all becoming companies. 30 posts between 8 October and 6 November, all at 6 or 8 a.m. Eastern.
The LinkedIn algorithm shows a post to the people who reacted to the last ones, then to people like them. AI is the most crowded topic on the feed: the owners who'd buy read it, and so does everyone selling AI advice, courses and content. Reach can't tell them apart. Who reacted can. We looked at the first 100 people who reacted to each post and sorted them by role.
30posts in a month
1,186people reacted
200founders and executives
24came back 3+ times
Audience by roleThe 1,186 people who reacted, by roleFree
AI creators, coaches, consultants & advisors400 · 33.7%
Everyone else586 · 49.4%
Peers are the largest named group: 400 AI creators, coaches, consultants, advisors and LinkedIn growth experts, twice the number of buyers. Many of them come back every day. They push reach, and they rarely hire an operator.
The 200 founders and executives are the people the advisor writes for: owners of distributors and service firms, CEOs, COOs and finance leaders. Some of them build AI products and sell to the same owners, so not every one is a buyer.
SeniorityAll people who reactedFree
Founder, owner, C-level24.3%
Director, VP4.4%
Manager9%
Independent6.7%
Other55.6%
IndustriesFounders and executives onlyNetwarm
AI, software and tech51%
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See all industries and company sizes in your free scan.
Core audience24 founders and executives engaged 3+ times · 15 engaged 5+ timesNetwarm
24 founders and executives keep coming back. One of them reacted to 19 of the 30 posts.See your regulars
Engager company sizeEveryone who reacted, by company sizeNetwarm
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See which company sizes your founders and executives work at.See company sizes
02
What to post on LinkedIn to reach founders and executives
An advisor who sells shouldn't judge a post by its reactions. The most-reacted post on this profile is not the one that brought the most buyers.
We tagged each of the 30 posts by topic, then measured the share of founders and executives among the people who reacted.
Your topicsWhat your 30 posts were aboutFree
30posts
We are all becoming companies8
AI adoption inside companies7
Leadership & operating lessons6
AI economy & big tech6
Building in public3
Topics that attract founders and executivesShare of each topic’s reactions from founders and executivesNetwarm
AI economy & big tech18.5%
AI adoption inside companies15.8%
We are all becoming companies15.6%
Leadership & operating lessons14.3%
Building in public12.2%
One topic brings 1.5x more founders and executives than another. See which.See which topics
Breakdowns of the AI economy brought the highest share of founders and executives, 18.5%, and build-in-public posts the lowest, 12.2% (on 3 posts). The other three topics sit between 14% and 16%.
Posts that brought the most founders and executivesShare of founders and executives in each post’s reactions1 of 5 open
#1The most expensive words in AI: “Regardless of actual usage.”26.8%
#2A map of AI startups in San Francisco: build there or not?20.6%
#3The plan you had for your career needs an update20.5%
#4AI makes execution faster. Understanding the problem decides the value.20.2%
#5The AI Empire Builders are burning through billions19.6%
For comparison, the farmhouse-with-good-Wi-Fi post drew 337 reactions, the third most of the month, but 14.1% founders and executives.
6 rules for LinkedIn engagement from founders and executives
These rules come from what worked on the advisor's own profile, and from the best-performing posts by AI operations and transformation advisors on LinkedIn over the last 3 months.
1
Lead with the number an owner would check twice. A dollar figure with a catch in it (“regardless of actual usage”) stops owners who sign leases and hire against forecasts. Then bring it back to their own business in one line.On this profile: the Anthropic S-1 post brought 26.8% founders and executives, the highest share of the 30 posts.
Ask the question owners argue about. A short post with one real choice (move to the crowded market, or build locally?) gives owners a reason to answer from their own experience. Two lines can be enough.On this profile: the two-line San Francisco map post brought 20.6% founders and executives, the second highest share.
Put the problem inside one company. “Consider a company where revenue is growing, but profitability is falling.” A single company, with sales, operations and finance each blaming someone else, lets an owner see their own business before the lesson arrives.On this profile: the revenue-up, profit-down company scene brought 20 founders and executives, 20.2%. Across the niche: Jyothish Nair's two-company comparison drew 1,011 likes and 273 comments.
Name the person every company has. “Every company has a Gary.” A name turns an operating problem into something people repeat in their next meeting, and tag their own Gary in the comments.On this profile: the Gary post drew 448 reactions, the most of the month, with 18.2% founders and executives.
Tie every build to the reader's business, not your toolkit. Build posts show the work, but an owner needs to see their own company in it: the tasks that disappeared, the cost, the decision that stayed human. Lead with the business result, then the tools.On this profile: build-in-public posts brought 12.2% founders and executives, the lowest topic. The Supabase post, built around what to buy and what to build, reached 18.4%; the Grok Bot team post, 11.9%. Across the niche: Nick Saraev's “$1M a year business” build drew 237 likes and 494 comments.
Offer the worksheet behind the advice. Owners don't need another explanation. They need a page they can fill in for their own company this week, and the ones who ask for it tell you who is serious.Across the niche: Kevin Lau's AI workbook for customer success leaders, one worksheet per section, drew 1,562 comments on 139 likes.
When founders and executives read: the best time to post on LinkedIn for AI operations advisors
We compared the share of founders and executives by the day and the hour each post was published (Eastern time). The advisor posts every day, so each weekday has 4 or 5 posts behind it.
Share of founders and executives by posting dayAmong the people who reacted to each postFree
14.0%
Mon
15.4%
Tue
17.3%
Wed
16.6%
Thu
16.4%
Fri
16.8%
Sat
12.3%
Sun
Best time to post, by hourShare of founders and executives among people who reactedFree
16.0%
6:00
15.7%
8:00
Wednesday brought the highest share of founders and executives (17.3%, 16.5 per post) and Sunday the lowest (12.3%, 5.8 per post). Saturday held up well, at 16.8%.
The 6 a.m. and 8 a.m. Eastern slots perform the same (16% and 15.7%), so keep the time that fits the morning. Put the posts that sell the work (the company scene, the worksheet) on Wednesday or Thursday, and keep Sunday for lighter posts.
05
5 posts ready to publish to target founders and executives
Each post follows the rules above, in the advisor's voice. Swap in your own details before posting: the real client story is what makes it land.
1Ready to postNamed pattern
Every company has a Friday ReportRule 4: name the thing every company has. Modelled on the Gary post, the most-reacted post of the month.
Hook
Every company has a Friday Report. Nobody reads it.It goes like this.Someone pulls numbers from three systems on Thursday night.
Pastes them into a template built in 2019.
Fixes the formulas that broke since last week.
Sends it Friday at 9.Six hours a week. 312 hours a year.Then leadership buys an AI tool, and the first use case on the list is…automating the Friday Report.Here's the problem.If nobody acts on the report, AI just produces an unread report faster.That's not a technology problem.
It's an operating problem wearing a technology costume.Before you automate any recurring report, ask four questions:✅ Who opened it last week?
✅ Which decision changed because of it?
✅ Which number would someone miss if it disappeared?
✅ Who would notice first?If the answers are “nobody,” “none,” and “no one,” you don't need an agent.You need permission to stop.In my work with companies, the fastest AI win is often deleting work, not accelerating it.Then automate the one number people actually use, and send it to the person who acts on it.AI is a multiplier.
Make sure you're multiplying something.What's the Friday Report in your company?
Visual · Meme or single imageA tired employee hitting send at 9 a.m. Friday, and an inbox where the report sits unopened. Funny image, serious point.Check before postingThe 6 hours a week is an example: use a real report from your own advisory work if you have one.
Two distributors, the same AI budgetRule 3: put the problem inside one company (here, two). Modelled on Jyothish Nair's two-company comparison and the revenue-up, profit-down post.
Hook
Two distributors. Same size. Same AI budget. One year later, only one is better.Company A buys licenses for everyone.Sales writes proposals faster.
Purchasing processes orders faster.
Finance builds reports faster.Every department gets faster.The quote still waits two days for a margin check.
The custom order still breaks the schedule.
The report still lands on a desk nobody reads.Company B starts somewhere less exciting.It picks one process that touches revenue: the customer quote.It writes down how a quote really moves, not how the SOP says it moves.It finds the steps living in two people's heads.
It decides who can approve what, and up to which number.Then it automates the version it can explain out loud.Company A has better tools.
Company B has a better operation.I ran an industrial distributor. I know which one I'd rather compete against.AI makes execution faster.
It doesn't decide what's worth executing.That's still the operator's job.Which company are you building right now?
Visual · Single imageTwo columns, Company A and Company B: the same AI budget at the top, five steps under each, a slow quote on the left and a fast quote on the right.Check before postingKeep the companies illustrative, or use a real (anonymous) client if you have one with this shape.
The most expensive line in your SaaS contractsRule 1: lead with the number an owner would check twice, then bring it home. Modelled on the Anthropic S-1 post, the highest share of founders and executives.
Hook
The most expensive line in your software contracts:
“Auto-renews for 12 months.”Anthropic signed minimum commitments that apply regardless of actual usage.Most companies did the same thing. Just smaller. And without an S-1 to make them read it.Here's what I find when I open the software list with an owner:✅ A CRM nobody updates since the sales manager left.
✅ Seats for people who no longer work there.
✅ Three tools doing the same job in three departments.
✅ A renewal date nobody owns.Then we talk about AI, and the first question is always:“Where does the budget come from?”Often, from right there.Buy the commodity stuff: email, payroll, accounting.
Build the layer that encodes how your business actually works.
Cancel what nobody opened this quarter.Because buying capacity creates two jobs:Use it.
Or keep paying for it anyway.That is where my operator brain stops scrolling.When is your next software renewal, and who decides whether it happens?
Visual · Single imageA contract clause highlighted in yellow: “Auto-renews for 12 months.” Nothing else.Check before postingThe four findings are typical examples: swap in what you really see in client software audits.
What I stopped building for clientsRule 5: tie the build to the reader's business, not the toolkit. Modelled on Nick Saraev's “$1M a year business” post and the Supabase post (18.4%).
Hook
This year I stopped building dashboards for clients. Here's what I build instead.I've built AI-native CRMs, valuation software, ERP modules and data reservoirs this year, for my own companies and for clients.The screens are the cheap part.I can rebuild a dashboard in an afternoon.Deciding what each field means, who can change it, and who gets to see it takes months.No model will make those calls for your business.So the first thing I build for a client now isn't software.It's a one-page answer to five questions:1️⃣ What is a customer? (Sales and finance usually disagree.)
2️⃣ What is an order, and when is it “done”?
3️⃣ Which number does the owner check every Monday?
4️⃣ Who is allowed to change a price?
5️⃣ Where does that information live today?Once those answers exist, the build goes fast.Without them, AI builds you a beautiful dashboard of numbers nobody trusts.Buy the commodity stuff.
Build the layer that encodes how your business works.
Write the definitions before either.Which of those five questions would start an argument in your company?
Visual · CarouselSlide 1: the hook. Slides 2–6: one question each, with the disagreement it usually causes. Slide 7: “Buy the commodity. Build the layer. Write the definitions first.”Check before postingUse the definitions you really start with in client work. Keep client names out.
Find your Gary's file in 30 minutesRule 6: offer the worksheet behind the advice. Modelled on Kevin Lau's workbook, built from the steps in the Gary post.
Hook
Find your Gary's file before your AI pilot does. It takes 30 minutes.Last month I wrote about Gary: one file, on one laptop, that quietly runs a real part of the business.The question I got most afterward:“How do I find ours?”So I turned the method into a one-page worksheet.Pick one process that touches revenue. The customer quote is a good start.Then answer five questions, with the people who do the work, not the people who manage it:1️⃣ Where does the number come from? Name the file, the system or the person.
2️⃣ Who touched it last, and when?
3️⃣ Which step is written down nowhere?
4️⃣ What happens if that person is out for two weeks?
5️⃣ Can you explain the whole process out loud, in order?If question 5 gets a long silence, you've found your Gary.Don't automate it yet.Write it down. Pay the person holding it to hand it over, in money or in status.Then automate the version you can explain out loud.AI is a multiplier.
Multipliers need something to multiply.Want the worksheet? Comment “GARY” and I'll send it to you.
Visual · Single imageThe worksheet itself: five numbered questions with blank lines, and “Process: customer quote” filled in at the top.Check before postingPut your Netwarm Reveal link in the reply so you can see which founders and executives download the worksheet.
Free forever: unlimited scheduling through LinkedIn’s official API, with images, video and PDF carousels.
06
LinkedIn lead generation: lead magnets that work to target founders and executives
Reactions show interest. A download shows intent. The fastest way to find out which owners are serious is to give them something they can use in their own company, and see who takes it.
In AI operations and adoption, these formats get the most requests:
Format 1The workbookOne worksheet per decision, filled in for the reader's own business: which work should touch AI, what it costs, how to report it.
Format 2The ready-to-run systemThe folders, prompts and steps behind one business function, ready to load into an AI assistant.
Format 3The one-page cheat sheetThe frameworks leaders have heard of, on one page they can print and bring to the next meeting.
Format 4The step-by-step guide for one teamOne real workflow per tool, for one department, written for the people who do the work.
Our pick for you: “The Gary File Audit”A one-page worksheet built from the steps the advisor already gave in the Gary post: pick one process that touches revenue, write down how it really runs, find who holds the missing steps, then automate the version you can explain out loud. Offer it in post 5, to the 448 people who already reacted to Gary.With a Reveal link, every person who downloads it is shown by name, with their role and how warm they are. Your first Reveal link is free.Create your free Reveal link
07
From reactions to clients
Content brings founders and executives to the profile. It doesn't say when to reach out. Most never comment, so they stay invisible, and an owner reading every post in October may have hired another advisor by January.
On LinkedIn, the right moment to start a conversation is when someone keeps coming back. We call that Hot: 5 or more points over 90 days, where a reaction counts 1, a repost 2, a download or a reply 4.
Hot right now15 founders and executives · not contacted yetNetwarm
15 founders and executives are Hot. See who to message first.See who’s Hot
First messageAn opener for each Hot person, based on the posts they readNetwarm
Hi Jordan, you've been reading my posts on AI and operations for a few weeks. Is there a Gary's file in your company too?Hi Sam, I saw you reacted to the post about software renewals. Is that conversation on your list before year end?
A first line for each of them, ready to send.See the openers
Netwarm sends nothing for you. It tells you who and when, and you write the message. It also works inside Claude and ChatGPT: ask “Who's Hot today?” and get the list.
08
FAQ
Posts that put an owner's own company on the page: a dollar figure with a catch, one company scene, a named pattern like “Gary's file”, and a worksheet they can use this week. Here, AI economy breakdowns brought 18.5% founders and executives and build-in-public posts 12.2%.
For this advisor, Wednesday brought the highest share of founders and executives (17.3%) and Sunday the lowest (12.3%). Thursday, Friday and Saturday were close behind Wednesday. Posting at 6 or 8 a.m. Eastern made no difference.
This advisor posts every day, and 24 founders and executives came back 3 times or more in a month. Daily works when each post gives owners something to use. Keep the posts that sell the work for midweek.
Look at who reacts, not how many. Here the most-reacted posts were not the ones with the most buyers. Group reactions by role, measure the share of your ideal clients per post, and follow the people who keep coming back. A free Netwarm scan does this for you.
Yes. Netwarm only reads public reactions to your own posts. It never logs in as you, never asks for your password, and never messages anyone for you.
How we made this playbook
We read the public reactions on 30 posts published between 8 October and 6 November 2026, the first 100 people on each post, and sorted the 1,186 people by role. Comments were not counted, so engagement figures are a floor. The newest posts were still collecting reactions.
Niche rules come from top posts by AI operations, strategy and transformation advisors over the last 3 months. Role groups are approximate, and some founders sell AI to the same owners; a Netwarm scan matches people to your own ideal client.
