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Paweł Huryn

Paweł Huryn

LinkedIn Content Strategy & Writing Style

AI PM | Deep research. I build, test, then teach | 130K+ subscribers

Poland
8 Viral ScoreView on LinkedIn

0 people tracking this creator on ViralBrain

Warm Analysis

Paweł Huryn positions himself as the definitive bridge between deep product management theory and the technical frontier of AI implementation. He moves beyond generic prompt engineering to advocate for intent engineering, treating AI agents as empowered team members rather than simple task executors. His content strategy centers on rigorous, data-backed experimentation—such as auditing model costs per "finding" rather than per token—and providing high-utility, open-source resources like his trending GitHub repositories. What makes Paweł notable is his "build, test, then teach" ethos, which replaces fluffy AI hype with production-ready infrastructure like CLAUDE.md templates and deployment tools. He occupies a unique intersection of technical product leadership and radical transparency, freely sharing the specific scripts and workflows he uses to move AI from a desktop demo to a scalable business asset.

Performance Overview

Followers

238.1K

Connections

30.0K

Avg. Engagement

164

Engagement Rate

Posts/Week

Viral Score

8

Posts Analyzed

1

Top Posts by Engagement

Just shared PM Skills v2.0 with 9 plugins, 68 skills, 42 commands. Free, MIT. You get the rigor of Teresa Torres, Marty Cagan, and Alberto Savoia built into your daily workflows. The open-source rep…

LinkedIn post image: Just shared PM Skills v2.0 with 9 plugins, 68 skills, 42 commands. Free, MIT.
1.4K419210 viral
Product Management4 months ago
View on LinkedIn

How to set up Claude Code as a PM (no coding). 5 steps. Free template at the bottom. 1. Install the Claude Code extension in VS Code → VS Code → Extensions → search "Claude Code." → Install. Sign in…

LinkedIn post image: How to set up Claude Code as a PM (no coding).
1.2K44788 viral
AI Productivity5 months ago
View on LinkedIn

I open-sourced the second brain for product managers. Sibling repo to pm-skills (11K stars on GitHub). Memory layer to its workflow layer. Folder of markdown files in a git repo. The agent reads the…

LinkedIn post image: I open-sourced the second brain for product managers.
1.0K53748 viral
Product Management5 months ago
View on LinkedIn

Aakash asked me how I actually use Claude as a PM. Here are the 10 steps I walked through on the Growth Podcast: 1. Replace Chat with Cowork → For anything beyond grammar checks. Cowork accesses you…

LinkedIn post image: Aakash asked me how I actually use Claude as a PM.
67333314 viral
AI Productivity5 months ago
View on LinkedIn

AI didn't make ideas the bottleneck. It made output free. Judgment stayed scarce. --- Execution used to be the filter. AI removed it. Now anyone can produce code, copy, designs, whole products at n…

LinkedIn post image: AI didn't make ideas the bottleneck.
50877204 viral
AI Strategy4 months ago
View on LinkedIn

How to set up Claude Code as a PM (no coding). 5 steps. Free template at the bottom. 1. Install the Claude Code extension in VS Code → VS Code → Extensions → search "Claude Code." → Install. Sign in…

LinkedIn post image: How to set up Claude Code as a PM (no coding).
46248213 viral
AI Tools4 months ago
View on LinkedIn

Posting Patterns & Frequency

5.0 posts/week

Posts / Week

1

Total Posts Analyzed

HIGH

Posting Frequency

Timezone: Europe/Warsaw

Best Performing Days

TuesdayWednesday

Best Performing Times To Post

Morning (08:00 - 10:00 CET)

Topics & Content Focus

Primary Topics

AI-Native Product ManagementProduction-Grade AI Agent ArchitectureLLM Context Engineering (CLAUDE.md)Strategic AI Deskilling & Human Judgment

Secondary Themes

No-Code App Development for PMsAI Evaluation & Guardrail ImplementationWorkflow Automation (n8n, Claude Code)Memory Systems for Self-Improving LLMs

Industry Focus

B2B SaaS Product ManagementAI Engineering for Non-Technical LeadsEnterprise AI Strategy

Content Categories

Technical Deep-DivesPhilosophical Industry ShiftsStep-by-Step Implementation GuidesCourse/Cohort Promotion

Performance Insights

163.9%

Avg Engagement Rate

STABLE

Performance Trend

Best Performing Topics

Step-by-step technical setups (Claude Code)Memory and Knowledge systems for LLMsAI Agent production vs. demo gaps

Virality Signals

Free template links in the main bodySpecific tool recommendations (VS Code, OpenRouter)Challenging 'best practices' (e.g., prompts don't matter)

Structure & Quality

1200

Avg Length (Words)

HIGH

Depth Level

ADVANCED

Expertise Level

0.9/10

Uniqueness Score

Common Hooks

The Counter-Intuitive Insight (e.g., AI making doctors worse)The Skill-Gap Provocation (e.g., 95% of PMs haven't built agents)The 'No-Code' Technical PromiseThe Framework Deconstruction (e.g., Deleting prompt templates)

Common Endings

Direct link to free resource/templateCohort launch countdown (Claudathon)Philosophical summary statement

Value Delivery Methods

Immediate utility via templatesMental model shifts for career longevityBridging the gap between PM and Engineer

Formatting Style

Single-sentence paragraphs for readabilitySymbol-heavy lists (→)Clear separation between insight and P.S. sections

Audience & Tone

YES

Question Usage

0.8%

Response Rate

Detected Tone

PragmaticTechnically ProficientContrarianHigh-Velocitysemi-formalfirst-person

Interaction Style

Authoritative EducatorResource CuratorStrategic Provocateur

Community Building Signals

Claudathon cohort mentionsFree 'no-paywall' resource sharingStandardizing PM-specific AI commands

Writing Style Patterns

Content Strategy

Hook: The Counter-Intuitive Insight (e.g., AI making doctors worseTone: semi-formalCTA: Resource-led (Free templates/guides)

Writing style breakdown

The author writes with the voice of a 'Pragmatic Visionary'—someone who is deeply technical but communicates through the lens of business value and product management (PM) strategy. The core characteristics are professional, punchy, and authoritative. It is a 'show, don't tell' style that uses data and personal experiments to back up bold claims.

Tone and Energy: The writing is high-energy and fast-paced. It feels like a series of 'dispatches from the front lines' of AI development. It is urgent but controlled, moving quickly from a surprising observation to a strategic takeaway.

Signature Traits: The author relies heavily on 'The Reversal'—taking a common belief (e.g., 'AI makes us worse') and flipping it ('That's not the story'). They use 'The Gap'—highlighting the difference between a demo and production. Rhetorical questions are rare; instead, the author uses 'The Direct Assertion' to create authority.

Addressing the Reader: The author uses a mix of second-person ('You') to give commands and first-person ('I') to establish credibility through personal testing. The relationship is mentor-to-peer. Suggestions are rarely soft; they are framed as 'The only way to win' or 'What matters is...'

2. STRUCTURAL FLOW & LOGICAL PROGRESSION
3. SPACING, LINE BREAKS & VISUAL FLOW
4. SENTENCE CONSTRUCTION & PACING

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