The 'Hidden Pattern' Prompt

How to Make Complex Tech Predictions Instantly Viral

There's a post structure that makes controversial tech predictions feel inevitable.

It's not data-driven analysis. It's not expert quotes. It's something that bypasses logical objections and speaks directly to pattern recognition.

The framework?

Using unexpected historical analogies from completely unrelated fields to make your tech prediction feel like it already happened.

It's like showing people the future through the past.

Why it's crushing it? Because it transforms abstract fears into concrete patterns:

• Skeptics can't argue with history that already happened.

• Readers see the pattern instead of debating the prediction.

The analogy does the heavy lifting while you look insightful.

And everyone remembers the comparison forever.

Here's a prime example from a recent post:

Link

Bjorn had 1.4k followers when he posted about Swedish carpenters.

Not Swedish tech. Not Swedish startups. Swedish home renovation TV from the 90s.

48 hours later: 2.9k followers. One historical analogy nearly doubled his audience.

Let’s see why this format worked so well.

🧠 The Psychology Behind Hidden Patterns

The Pattern Recognition Hack

Our brains are prediction machines that love patterns.

When you show a pattern from Field A (home renovation) that matches Field B (software development), the brain automatically completes the pattern. It's not a conscious choice - it's neurological autopilot.

Readers think they're drawing their own conclusions when really you've architected the only logical path.

The Emotional Distance Buffer

Tech predictions trigger defensive responses.

"AI will change everything" makes engineers defensive.

But "Remember what happened with Swedish carpenters?" creates emotional distance. They're analyzing history, not defending their future.

This buffer lets controversial ideas slip past mental defenses.

The Memorability Multiplier

Abstract predictions fade. Concrete stories stick.

No one remembers "AI will increase demand for engineers by 47%."

Plenty will remember "that Swedish renovation show that created a carpenter shortage."

The unexpected comparison becomes a mental bookmark readers can't forget.

🧱 Anatomy of the Perfect Hidden Pattern

Let's break down why this post structure works so brilliantly:

The Direct Contrarian Opening

AI "vibe" coding will cause a surge in demand for software engineers.

This opening:

• Makes a clear, memorable claim that demands explanation (authority)

• Drops the controversial take immediately -no warming up (surprise)

• Contradicts the dominant narrative everyone's hearing (curiosity)

The Context Bridge

My LinkedIn feed was full of AI coding predictions today, so here's mine:

This bridge:

• Positions you as joining an existing debate

• Sets up your take as one voice among many (humble positioning)

• Grounds the post in current conversations (not random theorizing)

The Expanded Prediction

I predict that AI's productivity boost in programming will increase the need for software, devops and MLops engineers, not replace them.

This prediction:

• Acknowledges the obvious truth (AI boosts productivity)

• Flips only the conclusion (smart contrarian, not delusional)

• Uses "not replace them" to directly address the fear

The Pattern Story

Years ago, a Swedish TV show showed the country how easy it is to renovate your house. Lots of people got inspired to renovate their houses by themselves. As people failed to complete these renovations, demand for carpenters and other trades skyrocketed.

This analogy:

• Shows clear cause-and-effect anyone can follow

• Includes the crucial word "failed" (acknowledges reality)

• Uses a completely unrelated field (prevents defensive reactions)

The Direct Connection

I think the same thing is going to happen for vibe coding and software engineers.

This connection:

• Keeps it simple (no complex explanation needed)

• Makes the pattern application explicit

• Uses "I think" for personal tone

The Practical Conclusion

Lots of people will use AI to build tools, websites, etc. Someone will have to maintain and improve those. The need for good software engineering practices, maintenance, troubleshooting, etc. is going to be higher than ever.

This conclusion:

• Uses inevitable logic ("someone will have to")

• Expands beyond fixing to maintaining and improving

• Ends on an optimistic note for engineers

🪜 Step-by-Step Implementation Guide

This step-by-step is for free subscribers who want to craft their own contrarian analogy posts. If you're a paid subscriber, feel free to jump straight to the prompt template - it'll do the heavy lifting for you.

Step 1: Identify the Controversial Prediction

(30 seconds)

Pick a tech prediction that triggers emotional responses:

• Industries being disrupted

• Jobs being eliminated/created

• Skills becoming obsolete/essential

Step 2: Find Your Historical Twin

(5 minutes)

Search for non-tech examples with similar patterns:

• DIY movements that created expert demand

• Automation that increased human jobs

• Simplification that led to complexity

Step 3: Build the Cause-Effect Chain

(2 minutes)

Map the historical pattern:

• Initial trigger (accessibility tool)

• Mass adoption phase

• Complexity revelation

• Expert demand surge

Step 4: Create the Direct Mapping

(2 minutes)

Connect each historical element to your prediction:

• Swedish DIY show = AI coding tools

• Amateur renovators = Vibe coders

• Failed projects = Broken production code

• Carpenter shortage = Engineer demand surge

Step 5: Add Specificity

(3 minutes)

Include:

• Exact numbers/percentages

• Timeline predictions

• Specific job titles affected

• Real company examples

Step 6: Write Your Closing

(1 minute)

Create one quotable line that encapsulates your entire argument:

AI makes starting easy. Easy starting creates complex failures.

OR

The pattern is clear. The only question is timing.

OR

Building is 10% of the work. Maintaining is 90%.

🔄 Advanced Variations

Variation 1: The Reverse Pattern

Start with the outcome and work backwards to show inevitability.

In 2010, Sweden had 47% more carpenters than in 2005. 

The reason? A home renovation TV show that aired 5 years earlier. 

Here's why AI coding tools are about to create the same surge in software engineers:

Variation 2: The "Everyone Missed This" Angle

Position yourself as the only one who sees the historical parallel.

Everyone's debating whether AI will replace programmers. 

They're asking the wrong question. 

I studied what happened when Excel 'replaced' accountants in the 1980s:

Variation 3: The Multi-Industry Pattern

Show the same pattern across 5+ unrelated industries for maximum proof.

The 'Accessibility Paradox' strikes every industry the same way:

📸 Instagram (2010): 'Everyone's a photographer!' 
→ Professional photography rates doubled by 2015

🎬 YouTube (2005): 'Anyone can make videos!' 
→ Video production became a $45B industry

📝 Blogging (2003): 'Everyone's a writer!' 
→ Content strategy emerged as six-figure career

💻 AI Coding (2024): 'Everyone can code!' 
→ [You already know what happens next]

Variation 4: The Personal Experience Bridge

I watched this movie before. 

In 2008, I was a video editor when Final Cut Pro 'democratized' video editing.

My boss said we'd all be unemployed within two years. 
Instead, I had to turn down work. 

Why? Every business suddenly needed video. 
They'd try it themselves, create unwatchable content, then panic-hire professionals to fix it.

❌ Mistakes to Avoid

Mistake 1: The Forced Analogy

Don't stretch connections. The parallel should feel obvious once stated.

❌ Bad: "AI coding is like the Renaissance because both involve creation..."
✅ Good: "AI coding is like WordPress - easy start, expert finish"

Mistake 2: The Academic Lecture

Keep it conversational. You're sharing an insight, not teaching history.

❌ Bad: "In 1847, the Industrial Revolution's mechanization of textile production..."
✅ Good: "Remember when ATMs were supposed to replace bank tellers?"

Mistake 3: The Weak Comparison

One powerful analogy beats five mediocre comparisons.

❌ Bad: "AI is like calculators, and smartphones, and the internet..."
✅ Good: "AI coding is like Instagram - everyone becomes a photographer until they need a real one"

Mistake 4: The Missing Bridge

Always explicitly connect the historical pattern to the current situation.

❌ Bad: Tell Swedish carpenter story, then jump to "AI is transformative!"
✅ Good: "Just like those DIY renovators, AI coders will need rescue"

Mistake 5: The Complexity Trap

Simple patterns work best. If it takes paragraphs to explain, find a better analogy.

❌ Bad: "It's like the Byzantine Empire's tax system reform of 1025..."
✅ Good: "It's like GPS replacing maps but creating more drivers"'

💬 Here’s the Prompt