Why Your Brilliant Content Is Getting Ignored
And the 20-Minute Fix That Forces the Algorithm to Work for You
Your content is brilliant. The algorithm doesn't care.
But the algorithm isn't broken. You just don’t understand it.
You're focused on creating "good" content. The algorithm is focused on finding a "perfect match."
If it can't find that perfect match instantly, your content dies in the feed.
I learned this the hard way – 6 months of "valuable" content that averaged 1,500 views.
Then I discovered a framework so simple, I almost dismissed it.
But after implementing it, my engagement jumped 10x in 20 days.
Not because I became a better writer. Not because I posted more. Because I changed my focus.
Today, I'm sharing the exact framework that took me from invisible to 85,000 followers.
🎯 The Algorithm's Real Job
Here's what most creators get wrong about LinkedIn's algorithm:
It's not trying to promote "good" content.
It's trying to keep people scrolling.
LinkedIn makes money from ad revenue. More scrolling = more ads = more revenue. The algorithm's entire purpose is matching content to the people most likely to engage with it.
When your content is generic, the algorithm has no idea who to show it to. So it shows it to almost nobody.
But when your content is laser-focused? The algorithm knows EXACTLY who needs to see it. That's when the magic happens.
🔬 The 1-1-1 Framework
After analyzing hundreds of viral posts, I noticed a pattern. The highest-performing content always followed this formula:
→ Solves 1 Specific Problem
→ For 1 Specific Person
→ In 1 Specific Way
That's it. No complex strategy. No growth hacks. Just radical specificity.
Let me show you why this works:
❌ Generic Content (Algorithm Confused)
"5 Tips for Better Productivity"
Who is this for? Everyone and no one
What problem does it solve? Too vague
Algorithm decision: Show to random 100 people, hope for the best
✅ Specific Content (Algorithm Confident)
"How Senior Python Engineers Can Debug Memory Leaks 73% Faster"
Who is this for? Crystal clear
What problem? Exact pain point
Algorithm decision: Show to every senior Python engineer interested in performance
The algorithm isn't your enemy. It's a matchmaker.
Give it clear signals, and it becomes your distribution partner.
📝 The 20-Minute Implementation
Here's exactly how to apply this framework today:
Step 1️⃣: Pick Your Niche (5 minutes)
Ask yourself: "What topics can I create practical content about?"
Not theoretical knowledge. Practical, been-there-done-that expertise.
Examples:
❌ AI/ML (too broad)
✅ Building production RAG systems
✅ Debugging PyTorch memory issues
✅ Fine-tuning LLMs on consumer GPUs
Your test: Can you write 10 posts about this without googling? If yes, you've found your niche.
Step 2️⃣: Name Your Audience (5 minutes)
Who would benefit MOST from your knowledge?
Be specific:
❌ Tech professionals" (too vague)
✅ SaaS founders building their first AI features
✅ Senior engineers dealing with LLM deployment
✅ Junior data scientists transitioning to ML engineering
The key: If you can't picture them at their desk, struggling with a specific problem, you're not specific enough.
Step 3️⃣: Solve Specific Problems (5 minutes)
What exact problems keep your audience up at 3am?
List 3-5 painful problems:
“LLM latency is killing user experience”
“Fine-tuning costs are eating my runway”
“Can't get consistent outputs from my prompts”
“My RAG system hallucinates on production data”
Reality check: If you haven't personally solved this problem, don't write about it.
Step 4️⃣: Claim Your Positioning (5 minutes)
Combine everything into one clear statement:
"I create content that helps {Audience} in {Niche} solve {Key Problem}."
Examples:
I help ML engineers building RAG systems eliminate hallucinations in production
I show bootstrapped founders how to add AI features without burning runway
I teach senior Python devs to debug memory leaks in deep learning code
This becomes your North Star.
But it's more than a nice phrase. It’s a ruthless filter for every future content idea.
Before you write a single word, run your idea through this filter:
"Does this directly help {Audience} solve {Key Problem}?"
If the answer is "maybe" or "no," discard the idea. Immediately. No matter how clever you think it is.
Why?
Every post that passes this test is another clear signal to the algorithm.
It's a deposit into your "Authority Account." Each deposit compounds, teaching the algorithm to find you more of the right people.
Any post that fails is a withdrawal.
It confuses the algorithm, dilutes your message, and sabotages your own momentum. Don't just align with this statement; defend it with every post you publish.
💡 Why This Actually Works (And Why It Feels So Wrong at First)
I know exactly what's going through your mind right now, because these thoughts paralyzed me for 6 months:
"If I get too specific, I'll limit my audience."
"I need broad appeal to grow."
"What if I box myself in?"
That fear—the fear of being small—is precisely why I chased generic topics. It's why I wrote for "everyone." And it's the single biggest reason my content was invisible, averaging a soul-crushing 1,500 views per post.
Here's the counterintuitive truth:
1. The Algorithm Loves Clarity
When someone engages with your "debugging PyTorch memory leaks" post, LinkedIn knows to show them more of your content. And to show your content to similar people. The clearer your focus, the better the algorithm works for you.
2. Humans Crave Relevance
Generic advice feels like spam. Specific solutions feel like salvation. When someone sees content that addresses their EXACT problem, they pay attention and engage.
3. Authority Through Specificity
Would you trust a "general AI consultant" or someone who's solved your exact problem 100 times? Specificity builds credibility faster than credentials.
🧠 The Ultimate Reframe
Most creators fail because they're trying to impress everyone instead of helping someone.
The internet doesn't need another generic AI influencer. It needs someone who solves real problems for real people.
Your expertise isn't in knowing everything. It's in solving specific problems better than anyone else.
"But What if I want to pivot later?"
You can. I started writing about Data Science. Now I cover all of AI Engineering. But I earned the right to expand by proving expertise first.
"What if my niche is too small?"
If 1,000 people on the internet have your problem, that's enough. 1,000 engaged followers > 100,000 ghosts.
"What if I get bored?"
You won't. Going deep reveals infinite content opportunities. I have written 200+ posts about AI engineering and haven't scratched the surface yet. 👉 This framework shows you how to find your own goldmine.
Think of specificity as a wedge. You need a sharp point to break through the noise. Once you're in, you can expand the wedge as wide as you want.
But without that initial sharp point? You're just another blunt object bouncing off the algorithm.
The 1-1-1 framework isn't about limiting your potential. It's about focusing your impact so precisely that growth becomes inevitable.
🎯 Make Your Choice
You have two options:
Keep creating generic content for everyone (and reaching no one)
Spend 20 minutes getting specific (and watch your audience compound)
The algorithm is waiting. It wants to help you. But first, you need to help it understand who you serve.
Stop overcomplicating content strategy.
→ Solve 1 Specific Problem
→ For 1 Specific Person
→ In 1 Specific Way
That's your entire playbook.
The creators who win aren't the loudest. They're the most specific.
That’s it for now—more soon!
Catch you next time,
Creator of LinkedIn Audience Building for AI/ML Engineers
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