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I went from 0 to 100K followers in 10 months.
Almost entirely without video.
Here's the uncomfortable part.
Every video I posted outperformed everything else.
So why so few?
Because a 30-second video costs me 30+ minutes of filming.
And hours of editing after that.
That math is why creators quit.
Then I found the system to break it.
Here's how to create viral LinkedIn videos, step by step 👇
𝗦𝘁𝗲𝗽 𝟭. 𝗪𝗶𝗻 𝘁𝗵𝗲 𝗳𝗶𝗿𝘀𝘁 𝟮 𝘀𝗲𝗰𝗼𝗻𝗱𝘀.
→ A number with proof
→ A bold statement
→ A polarizing opinion
Start mid-thought.
Never say "hey everyone."
𝗦𝘁𝗲𝗽 𝟮. 𝗥𝗲𝗰𝗼𝗿𝗱 𝗿𝗮𝘄, 𝗼𝗻 𝘆𝗼𝘂𝗿 𝗽𝗵𝗼𝗻𝗲.
One idea per video.
3 to 5 minutes max.
Keep the filler words. You'll see why.
𝗦𝘁𝗲𝗽 𝟯. 𝗗𝗼𝗻'𝘁 𝗲𝗱𝗶𝘁. 𝗗𝗶𝗿𝗲𝗰𝘁.
Drop the raw footage into OpusClip's AI Producer: https://lnkd.in/epbdKDTJ
Type one line: "energetic, punchy, highlight the numbers."
→ Filler words and dead pauses, cut automatically
→ Captions animated to match your tone
→ Say a stat, it builds the chart
20 minutes later, it's post-ready.
𝗦𝘁𝗲𝗽 𝟰. 𝗥𝗲𝘃𝗶𝗲𝘄, 𝘁𝗵𝗲𝗻 𝗽𝗼𝘀𝘁.
Your real footage, your real voice, refined.
One review pass, tweak by chat, publish.
The editing excuse just died.
Swipe for the visual guide with screenshots 👇
1. Save this for your next recording.
2. Try it: https://lnkd.in/epbdKDTJ
#AIProducer
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Apple pays Google $1B. Google pays Apple $20B.
This meme is funnier when you know what's behind it 👇
Apple pays $1B a year to run its new Siri on Gemini tech.
Google pays $20B+ a year to stay the default search engine on iPhone.
Rivals, paying each other billions.
And it's happening everywhere in AI:
→ Nvidia invests $100B in OpenAI, OpenAI buys Nvidia chips.
→ Big Tech is spending $750B on AI buildout this year alone.
→ Money keeps circling between the same few companies.
That's exactly why the bubble warnings are getting loud:
→ A leaked US Treasury report privately compares AI to the dotcom era.
→ The BIS warns the bubble could pop and hit the global economy.
But here's my take as someone building in AI every day:
The dotcom crash killed the hype companies.
It made the real builders more valuable than ever.
Same thing happens if this bubble pops.
Wrapper apps and prompt tricks disappear.
Agents with real ROI, RAG systems, and evaluation skills become the safest career bet in tech.
So enjoy the meme.
Then make sure your skills survive both endings of this story.
Bubble or genius: what does this handshake look like to you? 👇
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7 AI workflows quietly save me +10 hours every week. This book gives you every prompt and template to run them yourself + FREE code repo
📖 "AI for Everyday Automation" by Dipankar Sarkar
The practical guide to saving hours every week with ChatGPT, Claude, and Perplexity
𝗪𝗵𝗮𝘁 𝘆𝗼𝘂'𝗹𝗹 𝗺𝗮𝘀𝘁𝗲𝗿:
1️⃣ 𝗘𝗺𝗮𝗶𝗹 & 𝗖𝗼𝗺𝗺𝘂𝗻𝗶𝗰𝗮𝘁𝗶𝗼𝗻
- Automate email triage and drafting
- Reach inbox zero in 25 minutes
- Keep your personal voice intact
2️⃣ 𝗠𝗲𝗲𝘁𝗶𝗻𝗴𝘀 𝗧𝗵𝗮𝘁 𝗪𝗼𝗿𝗸
- Generate summaries in minutes
- Extract action items automatically
- Follow-ups without the busywork
3️⃣ 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 & 𝗕𝗿𝗶𝗲𝗳𝘀
- Research in 30 minutes, not 3 hours
- Create structured briefs fast
- Use Perplexity for deeper digging
4️⃣ 𝗥𝗲𝗽𝗼𝗿𝘁𝘀 & 𝗗𝗼𝗰𝘂𝗺𝗲𝗻𝘁𝘀
- First drafts in 15 minutes
- Build reports with reusable prompt chains
- Proposals and business docs at speed
5️⃣ 𝗗𝗮𝘁𝗮 & 𝗦𝗽𝗿𝗲𝗮𝗱𝘀𝗵𝗲𝗲𝘁𝘀
- Analyze messy data without advanced Excel
- No formula writing required
- Extract insights fast
6️⃣ 𝗬𝗼𝘂𝗿 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱 𝗪𝗲𝗲𝗸
- Combine workflows into daily routines
- Reliable, repeatable systems
- Get your time back
✨ Bonus:
→ Ready-to-use prompts and templates
→ Step-by-step guidance for each workflow
→ No technical background required
👉 Get the book: https://amzn.to/4xHpaH2
🔗 Github repo: https://lnkd.in/eXVQQtxZ
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Everyone is racing to make AI write code faster.
Today CodeRabbit raised $143M on the opposite bet.
They believe the real problem starts after the code is written.
And they have a point.
An agent can open 50 pull requests overnight, but no team on earth can properly review all of them.
We've reached a strange moment where code exists before anyone decides if it should.
That decision, what actually gets merged, is quietly becoming the most valuable skill in software.
CodeRabbit is naming it a category: Agentic Change Management. The bet is that validating, prioritizing, and governing every change is the work that matters now.
They already run 2M+ reviews a week for 15,000+ teams, so the market clearly feels this pain too.
Knowing what not to ship is turning into a real competitive edge.
Full announcement below 👇
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We've seen this movie before.
In 2015, startups woke up to horrifying AWS bills.
Not because cloud was expensive.
Because nobody had designed for cost.
Servers running all night for nothing.
Databases sized for traffic that never came.
An entire industry, FinOps, was born just to clean up the mess.
In 2026, the exact same story is repeating with AI.
Teams ship agents that work beautifully in the demo.
Then the invoice arrives.
And it turns out the agent:
→ Rereads the full conversation history on every step
→ Calls a frontier model to do what a small model does fine
→ Burns thousands of reasoning tokens on decisions that were already obvious
The lesson from the cloud era applies word for word:
Infrastructure doesn't get expensive when you use it.
It gets expensive when you design without thinking about it.
The companies that survived cloud economics weren't the ones with the biggest budgets.
They were the ones who made cost a design constraint from day one.
The same filter is coming for AI products.
And it's going to be brutal for everyone who treated inference as free.
Were you around for the cloud bill shock era? Feels familiar, doesn't it?
