LinkedIn Taught Me What Works (And Why I Owe Brian Krebs an Apology)

**Author:** Patrick Duggan

**Reading Time:** 7 minutes

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# LinkedIn Taught Me What Works (And Why I Owe Brian Krebs an Apology)

I've published 58 blog posts in the last week. LinkedIn auto-cross-posts them all. The data is screaming at me.

**Top post: 1,506 impressions** - "Cloudflare Architecture: Krebs-Inspired, Not Krebs-Level (And Why That's Honest)"

**Bottom post: 28 impressions** - Various music analogies nobody asked for

The algorithm just taught me something about borrowed credibility, intellectual honesty, and why I need to apologize to Brian Krebs.

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The Data Doesn't Lie

**What worked (high impressions):**

- Krebs-Inspired Cloudflare post: **1,506 impressions** (3 likes, 23 hours)

- Token bill 84% cut: **315 impressions** (5 likes, 4 days)

- Code shops = signmakers analogy: **237 impressions** (3 likes, 1 day)

**What didn't work (low impressions):**

- Dell trilogy (monitors/EMC/asset stripping): **65-174 impressions**

- Music analogies (GG Allin/Iggy Pop, Yes, Siberian Khatru): **27-83 impressions**

- "I Caught the Guy Who Attacked Brian Krebs": **53 impressions** (14 hours)

That last one is the problem.

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The Outlier That Proves Everything

I wrote a post about identifying the infrastructure behind Brian Krebs' 620 Gbps DDoS attack from 2016. The attacker is now selling "DDoS protection" services. It's the biggest story I've published.

**53 impressions in 14 hours.**

Meanwhile, a post saying "I'm Krebs-INSPIRED but not Krebs-LEVEL" gets **1,506 impressions in 23 hours**.

**The lesson:** Humility + borrowed credibility > claiming you caught someone famous.

**The hypothesis I'm testing RIGHT NOW by publishing this:** Apologize publicly, show the math, explain the admiration = better engagement than claiming credit.

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Why I Owe Brian Krebs an Apology

**The context:** Brian and I both worked at The Washington Post. Different eras, different roles, but we're both plumbers. He covered security, I built infrastructure that could handle what he wrote about.

**The admiration:** When Brian got hit with 620 Gbps in 2016, it changed internet architecture. Cloudflare built Project Galileo because of him. I built my infrastructure inspired by his experience.

**The mistake:** Writing "I caught the guy who attacked Brian Krebs" sounds like I'm claiming credit for HIS story. I'm not. I'm saying:

1. Brian got attacked in 2016 (his story, his credibility earned through years of excellent reporting)

2. The attack came from specific infrastructure (documented, public knowledge)

3. That same infrastructure is now selling "protection" services (irony I noticed)

4. I built defenses inspired by what happened to him (my derivative work, standing on his shoulders)

**The apology:** Brian, I used your name for credibility I didn't earn. The post should have been "The Guy Who Attacked Krebs Is Selling DDoS Protection Now (The Receipts)." You earned the attention through decades of excellent security reporting. I'm just a guy who read your work and built infrastructure inspired by it.

We're both Washington Post plumbers. You're the one people remember. That's deserved.

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The Pattern LinkedIn Taught Me

**What gets engagement:**

1. **Concrete ROI numbers** - "84% token reduction" (315 impressions)

2. **Self-awareness** - "Krebs-inspired, NOT Krebs-level" (1,506 impressions)

3. **Visceral metaphors** - "Signmakers selling to the next business to fail" (237 impressions)

4. **Show the math** - Real measured data beats claims

**What doesn't get engagement:**

1. **Abstract music analogies** - GG Allin/Iggy Pop spectrum (45 impressions)

2. **Meta-commentary about writing** - How the blog works (30-50 impressions)

3. **Claiming credit for someone else's story** - Krebs attacker post (53 impressions)

**The lesson:** Borrow credibility honestly (Krebs-INSPIRED) = 1,506 impressions. Claim you caught someone famous = 53 impressions.

LinkedIn's algorithm rewards intellectual honesty. Or punishes borrowed valor. Same thing.

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The Experiment Running Right Now

**Hypothesis:** This post will outperform "I Caught the Guy Who Attacked Brian Krebs" because:

1. **Public apology** - Shows intellectual humility

2. **Shows the math** - Real LinkedIn impression data (1,506 vs 53)

3. **Explains admiration** - Washington Post plumbers, different eras

4. **Tests the theory publicly** - Invites validation/refutation

**Prediction:** This post gets 200-400 impressions within 24 hours (better than Layer3 post's 53, worse than Krebs-Inspired post's 1,506).

**Why that range:**

- Self-awareness posts work (1,506 impression proof)

- Apology posts get engagement (curiosity + respect)

- But meta-analysis posts underperform (30-50 impression pattern)

- Middle ground: 200-400

**How I'll know I'm right:** LinkedIn auto-cross-posts this. I'll report results in 24 hours.

**How I'll know I'm wrong:** <100 impressions = nobody cares about apologies, they care about Krebs name recognition only.

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What I Learned From a Week of Data

**From 58 blog posts and LinkedIn auto-cross-posting:**

1. **Borrowed credibility works when honest** - "Krebs-inspired" (1,506) > "I caught Krebs' attacker" (53)

2. **Show the math always** - Concrete numbers get engagement

3. **Self-awareness beats hype** - "NOT Krebs-level" performed best

4. **Visceral metaphors beat abstract ones** - Signmakers (237) > GG Allin spectrum (45)

5. **Controversial takes get READ but not LIKED** - Dell posts (65-174 impressions, 0-1 likes)

**The meta-lesson:** LinkedIn taught me what Brian Krebs already knew - earn credibility through consistent, honest reporting. Don't borrow it without acknowledgment.

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The Apology (Plain English)

Brian Krebs: I used your name in a headline to get attention for a story about infrastructure analysis. You earned that attention through decades of excellent security reporting and surviving a 620 Gbps attack that changed internet architecture.

I'm a guy who builds infrastructure inspired by what happened to you. That's derivative work, not original reporting.

We're both Washington Post plumbers (different eras). You're the one people remember because you did the hard work of investigative security journalism while getting attacked for it.

I should have led with admiration, not implied I caught someone you already wrote about years ago.

This is me fixing that.

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The Test Results (Update: 24 Hours)

**Publishing this post at:** October 24, 2025, 3:00 PM CT

**Prediction:** 200-400 impressions in 24 hours

**Actual results:** [Will update October 25, 2025, 3:00 PM CT]

**What this proves/disproves:**

- If >200 impressions: Apology + self-awareness works

- If <100 impressions: Only Krebs name recognition matters, not intellectual honesty

- If >500 impressions: Admitting mistakes beats claiming credit

**Auto-cross-post to LinkedIn:** Happening now (Zapier automation)

**Brian, if you're reading this:** Thank you for the example you set. Both in security reporting and in surviving what came with it. The infrastructure I built exists because you showed what was necessary.

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Addendum: Why This Matters

**The business lesson:** LinkedIn's algorithm rewards intellectual honesty over borrowed valor. The data proves it.

**The personal lesson:** Admiration expressed honestly beats credit claimed dishonestly.

**The Washington Post plumber lesson:** Some of us built the pipes. Some of us wrote the stories that mattered. Brian did the latter while surviving attacks from doing it well.

I'm just a guy who read his work and built better pipes because of it.

That's the truth. Let's see if LinkedIn agrees it's more interesting than claiming I caught someone famous.

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**Results update in 24 hours. The algorithm will tell us if apologies beat hype.**

**P.S.** - If this gets >1,506 impressions, I'll write "How Apologizing to Brian Krebs Outperformed Everything Else I Wrote" and test if meta-analysis of apologies beats the original apology. Recursion all the way down.

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*This post is part of the DugganUSA blog automation experiment. 58 posts published, all auto-cross-posted to LinkedIn, all performance tracked. The algorithm is teaching me what works. This is me learning in public.*

*Brian Krebs deserves the admiration. I'm just documenting the infrastructure lessons learned from his experience.*