Stijn Verhagen
Financial-services firms hire me instead of a marketing team. I install AI marketing systems, run it on your expertise and you never become the marketer. 95+ firms
Stijn Verhagen teaches B2B founders how to generate LinkedIn leads using AI systems instead of hiring agencies, positioning himself as the builder showing live systems rather than the theorist selling courses. His most distinctive move is the contrarian hook that directly attacks competitor pricing ($50K/year, $15K projects) while claiming he built the same thing in minutes, which generates 399 avg engagement per post.
5.7/wk
74 posts in 30d
147
avg per post
69.4%
comments / total
0.7%
reposts / total
problem-solution
Thu · 10 AM CET
Voice & tone
Stijn writes like a builder who's impatient with BS. He uses short, punchy sentences. He contrasts old ways (dying) with new ways (thriving). He name-drops competitors and their pricing to establish credibility through specificity, not ego. The tone is "I'm showing you the exact clicks" not "trust me, I know." He repeats "I'm done with the BS" and similar declarations to signal authenticity.
Signature phrases
- “I'm done with the BS.”
- “What takes agencies X weeks/months”
- “The results after [timeframe]:”
- “Why [competitor] crushed the competition:”
- “Stop chasing [vanity metric] and start building [real metric].”
- “I've built this system 100+ times.”
Top 3 posts, dissected
Their highest-engagement posts, broken down line by line. Steal the structure.
NEVER use GPT for LinkedIn content again… The new Gemini 3 prompt library replaces a $50,000/year ghostwriter Most founders struggle with LinkedIn lead generation. -Generic posts that get zero engagement. -Lead magnets nobody downloads. -No pipeline from content. I just built a Gemini 3 Promptlibrary based on 50M+ views and 10,000+ leads generated. The capabilities are insane: → Writes viral LinkedIn posts instantly → Creates lead magnets people actually want → Generates inbound leads on autopilot This isn't just theory - I've used this system across 100+ B2B niches. The best part? It costs $0 compared to a ghostwriter which would charge you $3,000 - $5,000 monthly I've included everything in the library: → Viral post frameworks → Lead magnet templates that convert → Hook formulas for maximum engagement → CTA structures that book calls Want the prompts? 1. Connect with me 2. Comment "GEM" below I'll send it straight to your DMs. PS - I just updated the library with 30+ new LinkedIn templates.
NEVER use GPT for LinkedIn content again stops the scroll because it contradicts what most readers are currently doing (using GPT). The word NEVER is absolute and creates immediate tension. The ellipsis signals a reveal is coming, pulling readers into the body.
Hook (NEVER...) → Problem statement (3 bullets of founder struggles) → Solution intro (I built a Gemini 3 library) → Capabilities list (4 arrows showing what it does) → Social proof (100+ B2B niches) → Price anchor ($0 vs $3-5K monthly) → What's included (4 arrows of templates/frameworks) → CTA (2-step: Connect + Comment GEM) → PS (social proof of recent update)
- Absolute language (NEVER, insane) to create conviction
- Arrow bullets (→) for scannable benefits instead of prose
- Price comparison in parentheses to anchor value without breaking flow
- Two-step CTA (Connect + Comment) to create dual commitment and DM capture
- PS with recency signal (just updated) to add urgency
The two-step CTA (Connect + Comment GEM) drives comments because it asks for a public action first (commenting), which triggers the algorithm and creates social proof. The DM follow-up captures contact info. The PS adds FOMO by mentioning 30+ new templates, making readers feel they're missing out if they don't act.
Use absolute language (NEVER, STOP) in your hook to create cognitive dissonance, then resolve it with a specific price comparison that makes your solution feel like a steal.
I tested ChatGPT vs Gemini 3 vs Claude for 30 days of LinkedIn content. The winner shocked me... Most founders waste 3-5 hours daily on content creation. - ChatGPT writes generic corporate fluff - Claude sounds too academic - Gemini 3? Different story entirely. I ran 30 clien…
I tested ChatGPT vs Gemini 3 vs Claude for 30 days works because it signals a controlled experiment (same prompts, same topics, same CTAs), which feels scientific and trustworthy. The phrase "The winner shocked me" creates curiosity by implying the result was unexpected. Readers want to know which tool won.
Hook (tested 3 tools for 30 days) → Reveal setup (same prompts/topics/CTAs) → Results table (3 tools with 3 metrics each: engagement rate, leads, viral posts) → Why winner won (4 bullets explaining Gemini 3's advantage) → Biggest difference (contrasts how each tool thinks) → Personal commitment (switched entire system) → CTA (Want my exact prompt framework)
- Comparison table with bold formatting (𝗧𝗵𝗲 𝗿𝗲𝘀𝘂𝗹𝘁𝘀 𝗮𝗳𝘁𝗲𝗿 𝟯𝟬 𝗱𝗮𝘆𝘀:) to make data scannable and credible
- Specific metrics (2.3% vs 8.7% engagement, 12 vs 127 leads) to make the winner undeniable
- Contrasting philosophy (ChatGPT writes what it thinks LinkedIn wants vs Gemini 3 writes what audience reads) to explain why, not just what
- Personal commitment (I've now switched my entire system) to signal the creator uses their own tool
- Truncated CTA (Want my exact Gemini 3 prompt framework that generated 127 le…) to create curiosity and force a click
The CTA is truncated intentionally ("127 le…") to force readers to click or comment to see the full number. This drives engagement because the reader's brain wants closure. The specific number (127 leads) is so high it feels almost unbelievable, which makes readers want to verify it in comments.
Use a comparison table with specific metrics to make your winner undeniable. Truncate your CTA to create curiosity loops that force engagement.
This Gemini 3 system replaces a $50K/year LinkedIn ghostwriter. (and it generates 4x the pipeline in 8 minutes a day) Most agencies charge $5,000/month for "mastery" and "optimization." I am done with the BS. I built a system that turns a single sentence into a lead-generating…
This Gemini 3 system replaces a $50K/year LinkedIn ghostwriter works because it immediately answers the reader's unspoken question: "How much will this cost me?" The price anchor ($50K/year) is so high it makes the reader lean in to find out the alternative. The parenthetical (and it generates 4x the pipeline in 8 minutes a day) adds outcome proof, not just cost savings.
Hook (replaces $50K/year ghostwriter) → Subheader (4x pipeline in 8 min/day) → Problem (agencies charge $5K/month for BS) → Solution intro (built a system that turns one sentence into a lead post) → What agencies charge (4 line items totaling $15K) → Social proof (built 100+ times) → System positioning (production-grade infrastructure, not content calendar) → What's inside (5 components with specific names like LinkedIn Empire Blueprint) → Call to action (Connect + Comment ORACLE) → PS (must be connected) → PS (Repost for 3-day training)
- Price anchor in headline ($50K/year) to establish the problem's cost
- Outcome in subheader (4x pipeline, 8 min/day) to show the benefit is real, not theoretical
- Line-item breakdown of agency costs ($3K, $2K, $5K, $5K) to make the problem feel itemized and real
- Reframing language (production-grade infrastructure, not content calendar) to elevate the offer beyond typical content tools
- Specific component names (LinkedIn Empire Blueprint, AI Fine-Tuned Content Agent) to make the system feel like a real product, not a vague promise
- Escalating CTAs (Connect + Comment + Repost for bonus) to create multiple commitment layers
The CTA uses a code word (ORACLE) instead of generic language, which makes the action feel exclusive and trackable. The PS about needing to be connected removes friction by explaining why the DM might fail. The repost bonus (3-day training) creates a secondary incentive for amplification, turning readers into distributors.
Use specific price anchors and line-item breakdowns to make the problem feel itemized and real. Use code words in CTAs to make the action feel exclusive and trackable.
What drives their engagement
Stijn's posts drive comments (69.4% of engagement is comments, not likes) because he uses truncated CTAs, specific numbers that feel unbelievable (127 leads, 8.7% engagement rate), and asks readers to verify claims by commenting. His contrarian claims also trigger debate in comments (people defending the old way vs agreeing with the new way).
Reposts are low (0.7%) because his content is highly specific to his niche (B2B founders doing LinkedIn lead gen) and his CTAs ask for comments and DMs, not shares. However, his post #3 includes a repost bonus (3-day training), which explains why it has 50 reposts vs the typical 2-7.
Low savability. Stijn optimizes for immediate action (comment, DM, connect) over long-term reference. His posts are time-sensitive (LIVE builds, new updates) and outcome-focused (book calls tomorrow), not educational frameworks readers would save for later.
Content pillars
AI-Powered LinkedIn Systems
35%Teaches founders how to use Gemini 3, ChatGPT, and Claude to automate content creation and lead generation instead of hiring ghostwriters or agencies.
Contrarian Comparisons
25%Compares old-school LinkedIn strategies (Justin Welsh's funnels, agency pricing models) to new AI-native approaches, positioning the new way as faster and cheaper.
Live Builds and Proof
20%Shows specific results from client projects (312 profile views, 47 qualified leads, $30k pipeline) to prove the system works, not just theory.
Lead Magnet and Funnel Mechanics
15%Breaks down the infrastructure behind converting LinkedIn posts into calls: profile optimization, lead magnet templates, automation workflows, and CTA structures.
Pricing Transparency
5%Repeatedly contrasts what agencies charge ($3K-$15K) with what his system costs ($0-minimal), using specific dollar amounts to anchor the value proposition.
Hook patterns
Contrarian Claim with Price Anchor
[NEVER/STOP] [common practice] because [new tool/approach] replaces [expensive service] at [fraction of cost]
“NEVER use GPT for LinkedIn content again… The new Gemini 3 prompt library replaces a $50,000/year ghostwriter”
→ Creates immediate cognitive dissonance (contradicts reader's current behavior) then resolves it with a specific price comparison that feels like insider knowledge.
Experiment Reveal with Shock Winner
I tested [X options] for [timeframe]. The winner shocked me... [Setup problem] [Results table with clear winner]
“I tested ChatGPT vs Gemini 3 vs Claude for 30 days of LinkedIn content. The winner shocked me...”
→ Positions the post as data-driven research, not opinion. The "shocked me" signals the result was unexpected, triggering curiosity. The comparison table makes the winner undeniable.
Time-to-Build Comparison
I spent [short timeframe] building [system] that does what [competitor/guru] does [with their timeframe/cost]
“I spent 17 minutes building an AI system that does what Justin Welsh's $10M funnel does. And it outperformed his entire setup in 48 hours.”
→ Combines speed (17 minutes) with social proof (named competitor) and outcome (outperformed). Creates FOMO and positions the creator as more efficient than established names.
Live Demo Urgency
LIVE! Watch me build [complete system] in [short timeframe] (while agencies charge $[large amount] for the same thing)
“LIVE! Watch me build a complete LinkedIn → Call system in 7 minutes (while agencies charge $15k for the same thing)”
→ The word LIVE creates scarcity and real-time urgency. The parenthetical price anchor makes the offer feel absurd (agencies = overpriced, creator = efficient).
Problem Statement with Specific Pain
Most [target] [struggle/waste time] with [problem]. [Bullet list of failures]
“Most founders struggle with LinkedIn lead generation. -Generic posts that get zero engagement. -Lead magnets nobody downloads. -No pipeline from content.”
→ Validates the reader's frustration before offering the solution. Specificity (generic posts, lead magnets nobody downloads) makes the pain feel real, not generic.
Old Way vs New Way Contrast
The [old way] (dying): [slow/expensive steps]. The [new way] (thriving): [fast/automated steps]
“The old way (dying): Pay someone → They promise results → You wait 3 months → Maybe get 5 calls. The system way (thriving): Watch me build it → Copy exactly → Launch same day → Calls tomorrow”
→ Binary framing (dying vs thriving) forces a choice. The arrow structure shows progression and causation. Adds emotional stakes (FOMO of being on the dying side).
Top-performing hooks
“NEVER use GPT for LinkedIn content again…”
“I tested ChatGPT vs Gemini 3 vs Claude for 30 days of LinkedIn content.”
“This Gemini 3 system replaces a $50K/year LinkedIn ghostwriter.”
→ The post uses a high-friction 'Comment for Access' mechanic to exploit the LinkedIn algorithm's preference for early engagement while positioning AI as a cost-saving alternative to expensive agencies.
“I spent 17 minutes building an AI system that does what Justin Welsh's $10M funnel does.”
→ It weaponizes a well-known creator's brand (Justin Welsh) as a contrast anchor to position the author's AI approach as superior, triggering curiosity and tribal debate in comments, while the explicit
“LIVE! Watch me build a complete LinkedIn → Call system in 7 minutes”
→ It uses a high-tension 'pattern interrupt' by comparing a $15k agency service to a 7-minute DIY build, then validates the claim with specific ROI metrics and a low-friction comment-to-receive CTA.
“STOP wasting $10k+/month on funnel builders and agencies...”
→ The post uses a high-friction 'stop wasting money' hook to grab attention and leverages the hype of advanced AI (GPT 5.2) to offer a high-value, low-effort solution. The 'Comment to Access' CTA create
“The most SHOCKING 17 minutes of 2025:”
→ The post weaponizes fear of obsolescence and FOMO to drive massive comment-based engagement (560 comments vs 106 likes reveals the 'Comment PLAYBOOK' CTA is the primary driver). It layers urgency thro
“No joke, I've completely shifted from ChatGPT to Claude Cowork for 100% of my LinkedIn.”
→ The post leverages a high-friction 'comment-to-receive' CTA which artificially inflates engagement metrics, while positioning Claude as a superior alternative to ChatGPT to create immediate curiosity.
“I analyzed the top 3 creators making $1M/year and realized they're all doing the same thing wrong.”
→ The post leverages name-dropping well-known creators to borrow their authority while positioning the author as superior, creating curiosity and controversy. The old-vs-new comparison framework with sp
“I stole 3 funnels that pull in $1 million a year each.”
→ The post leverages high-authority names like Justin Welsh and Lara Acosta to build instant credibility while using a 'comment-to-receive' mechanism that triggers the LinkedIn algorithm through high en
What works
- Contrarian claims with price anchors generate 399 avg engagement (29 posts). Example: "NEVER use GPT for LinkedIn content again… The new Gemini 3 prompt library replaces a $50,000/year ghostwriter." The specific dollar amount makes the claim feel researched, not just opinionated.
- Problem-solution format with social proof generates 248 avg engagement (40 posts). Stijn leads with a founder pain point (generic posts get zero engagement), then shows his solution (Gemini 3 library), then proves it works (100+ B2B niches, 127 leads generated). The social proof makes the solution feel inevitable.
- Comparison tables with specific metrics drive comments because readers want to verify the numbers. Post #2 shows ChatGPT (2.3% engagement, 12 leads) vs Gemini 3 (8.7% engagement, 127 leads). The gap is so large it triggers skepticism, which drives comments asking for proof.
- Two-step CTAs (Connect + Comment [CODE WORD]) generate more comments than single CTAs because they create a public commitment (commenting) before a private one (DM). The code word (GEM, ORACLE) makes the action feel exclusive and trackable.
- Truncated CTAs ("Want my exact Gemini 3 prompt framework that generated 127 le…") force clicks and comments because readers' brains want closure. The incomplete number creates curiosity loops.
- Time-to-build claims ("I spent 17 minutes building…") combined with competitor names (Justin Welsh, $10M funnel) generate 2,639 engagement because they position the creator as more efficient than established names while creating FOMO.
Steal this for your own LinkedIn
- Start your next post with an absolute claim that contradicts your reader's current behavior (NEVER, STOP, DONE WITH). Follow it with a specific price comparison ($50K/year, $15K) to resolve the tension. This formula generates 399 avg engagement for Stijn.
- Build a comparison table with 3+ options and 3+ metrics (engagement rate, leads generated, viral posts). Make the winner undeniable with specific numbers. Use bold formatting to make it scannable. This drives comments because readers want to verify the data.
- Use a two-step CTA with a code word instead of generic language. Example: "Comment ORACLE below" instead of "Comment below." This makes the action feel exclusive, trackable, and more likely to be followed.
- Include a social proof anchor early (I've built this system 100+ times, 50M+ views, 10,000+ leads generated). This signals you're not theorizing, you're reporting from experience. Place it after the problem statement and before the solution.
- Contrast the old way (dying) with the new way (thriving) using arrow structures to show progression. Example: "Old way: Pay someone → Wait 3 months → Maybe 5 calls. New way: Watch me build → Copy exactly → Calls tomorrow." This forces a choice and adds emotional stakes.
- Post 5.7 times per week on Thursday at 9 UTC. Consistency trains the algorithm to show your posts to your audience at predictable times. Stijn's 74 posts in 30 days means his followers see him as a daily resource, not a weekly check-in.
Compare Stijn with…
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Posting patterns
Stijn posts 5.7 times per week (74 posts in 30 days) with extreme consistency, treating LinkedIn as a daily publishing platform rather than a weekly channel.
Thursday at 9 UTC performs best, which is mid-morning in European timezones and early morning in US timezones, catching both audiences during work hours.
Long-form posts (180-350 words) perform best for Stijn (64% of posts, 157 avg engagement), because his audience wants proof and specificity. Medium-length posts (80-180 words) also perform well (174 avg engagement), suggesting readers engage with both detailed breakdowns and punchy summaries. Very long posts (350+ words) underperform (78 avg engagement), indicating attention drops after 350 words.
Engagement by day
Content mix
avg 248 engagements per post
avg 39 engagements per post
avg 47 engagements per post
avg 107 engagements per post
avg 13 engagements per post
avg 14 engagements per post
Stijn's format mix (20% problem-solution, 17% story, 15% text) works because his audience wants proof and specificity, not inspiration. Problem-solution posts perform best (248 avg engagement) because they show a founder pain point, then immediately offer a system to fix it. Story posts underperform (39 avg engagement) because his audience doesn't want narrative, they want results. The high volume (5.7 posts/week) trains followers to expect daily content, making each post feel like a resource drop rather than a rare insight.
