30x-growth-marketing-panel

30x Growth Marketing Panel

Skill by ara.so — Marketing Skills collection.

An AI-powered expert panel of 11 world-class marketing experts distilled from 4,000+ YouTube videos. Get answers from the right expert(s) in their voice, using their actual frameworks.

What It Does

The 30x Growth Marketing Panel uses a dual-layer architecture to provide authentic expert advice:

• Layer 1 (Brain): NotebookLM retrieval from 4,000+ indexed YouTube videos
• Layer 2 (Soul): Persona Protocol with expert personality, frameworks, and anti-patterns
• Semantic routing: Automatically matches your question to the right expert(s)
• Anti-hallucination: Retrieve-first protocol ensures responses are grounded in actual expert content

Installation

npx skills add norahe0304-art/30x-growth-marketing-panel

Works with Claude Code, Cursor, Codex, and 45+ AI coding agents.

The Expert Panel

Expert	Domain	Best For
Alex Hormozi	Offer creation, pricing, sales, scaling	SaaS pricing, value propositions, sales frameworks
Greg Isenberg	AI startups, community growth, vibe marketing	Community-led growth, AI product positioning
Neil Patel	SEO, paid ads, CRO, social media	Traffic generation, conversion optimization
Nathan Gotch	AI SEO, Search Everywhere Optimization	AI-powered SEO strategies, ranking tactics
Authority Hacker	AI content at scale, affiliate marketing	Content automation, affiliate revenue
Sabrina Ramonov	AI agents, automation workflows, MCP	Marketing automation, AI agent implementation
Liam Ottley	AI automation agency, client acquisition	Agency model, service packaging
Julia McCoy	AI writing, content strategy, brand building	Content creation, brand voice
Ryan Doser	AI marketing tools, practical implementation	Tool stack, workflow optimization
Growth Tribe	Growth hacking, experimentation, AARRR	Experimentation frameworks, funnel optimization
Dan Koe	One-person business, writing, personal brand	Solopreneur strategy, personal branding

Usage Patterns

Single Expert Consultation

Ask focused questions to get advice from the most relevant expert:

# Pricing question → routes to Alex Hormozi
"How should I price my B2B SaaS product?"

# SEO question → routes to Neil Patel or Nathan Gotch
"What's the best AI SEO strategy for 2026?"

# Content question → routes to Julia McCoy
"How do I build a consistent content voice?"

Named Expert Request

Explicitly request a specific expert:

"Ask Alex Hormozi about my offer: [describe your offer]"

"What would Neil Patel say about this landing page conversion issue?"

"Get Greg Isenberg's take on community-led growth for an AI tool"

Multi-Expert Roundtable

Broad strategic questions trigger multiple experts:

"How should I go to market with a new AI marketing tool?"
# Returns perspectives from Greg Isenberg, Neil Patel, Ryan Doser

"What's the best growth strategy for a bootstrapped SaaS?"
# Returns perspectives from Alex Hormozi, Dan Koe, Growth Tribe

Expert Knowledge Base Structure

Each expert has two components:

1. NotebookLM Brain (Raw Retrieval)

# 200-300 YouTube videos per expert
# Indexed in NotebookLM Pro (300 sources/notebook)
# Zero information loss from original content

2. Persona Protocol (Personality)

Located in expert_kb.md for each expert:

## Role
Who the expert is, their background, core expertise

## Thinking Models
Frameworks they use (e.g., Hormozi's Value Equation, AARRR funnel)

## Tone & Communication
How they speak, teaching style, personality markers

## Anti-Patterns
What they avoid, common mistakes they call out

## Retrieval Logic
How to search their NotebookLM notebook effectively

Anti-Hallucination Protocol

The panel follows strict retrieval rules:

1. Retrieve first: Must search NotebookLM before generating responses
2. Dual verification: Cross-reference retrieval with KB persona
3. Explicit marking: Extrapolations from core principles marked with ⚠️
4. Never fabricate: If an expert hasn't covered a topic, say so

Example output structure:

**Alex Hormozi's Perspective:**

[Retrieved content from NotebookLM]

Framework: Value Equation
- Dream Outcome: [specific to your question]
- Perceived Likelihood: [specific analysis]
- Time Delay: [specific analysis]  
- Effort & Sacrifice: [specific analysis]

⚠️ *Extrapolating from core principles:* [only if needed]

Distilling Your Own Expert

Use the distill_anyone.md prompt template:

# 1. Copy the prompt from distill_anyone.md
# 2. Change 3 variables:
#    - Expert name
#    - YouTube channel/playlist URL
#    - Domain expertise
# 3. Run in Claude Code

# The pipeline automatically:
# - Collects YouTube URLs with yt-dlp
# - Creates NotebookLM notebook
# - Bulk adds videos with notebooklm-py
# - Generates Persona Protocol KB
# - Creates semantic routing rules

Variables to Configure

EXPERT_NAME="Your Expert"
YOUTUBE_SOURCE="https://youtube.com/@channel or playlist URL"
DOMAIN="their core expertise area"

Key Commands

Query the Panel

# General query (auto-routes)
"[Your marketing question]"

# Named expert
"Ask [Expert Name] about [topic]"

# Multi-expert
"Get a roundtable on [strategic question]"

Inspect Expert Knowledge

# List all experts and domains
"Show me the expert panel"

# View expert frameworks
"What frameworks does Alex Hormozi use?"

# Check NotebookLM coverage
"How many videos are indexed for Neil Patel?"

Configuration

Language Support

Responses automatically match your query language. Framework names stay in English:

# Query in Spanish → Response in Spanish
"¿Cómo debería fijar el precio de mi SaaS?"

# Query in French → Response in French  
"Quelle est la meilleure stratégie SEO?"

Retrieval Depth

Adjust how many NotebookLM sources to search:

# Default: 5-10 most relevant sources
# Deep research: 20-30 sources (slower, more comprehensive)
# Quick answer: 3-5 sources (faster, still accurate)

Real Code Examples

Example 1: Pricing Strategy (Alex Hormozi)

Query:

"How should I price my B2B SaaS with a $10k LTV and 6-month sales cycle?"

Expected Response:

**Alex Hormozi's Pricing Framework:**

[Retrieved from NotebookLM: Hormozi's pricing videos]

**Value Equation Analysis:**
1. Dream Outcome: Enterprise efficiency gain (high)
2. Perceived Likelihood: 6-month cycle = trust-building needed
3. Time Delay: 6 months is long → charge more upfront
4. Effort & Sacrifice: Implementation complexity matters

**Pricing Recommendation:**
- Annual contract: $5,000-$7,500/year
- Upfront discount: 20% off for annual vs monthly
- Reduce time delay perception: 30-day quick wins
- Stack value: Implementation support included

**Hormozi's Principle:** "Charge for the dream outcome, not your cost"

Example 2: SEO Strategy (Neil Patel + Nathan Gotch)

Query:

"What's the best AI SEO strategy for a new marketing tool in 2026?"

Expected Response:

**Neil Patel's Take:**
[Retrieved content about AI content + E-E-A-T]

- Focus on helpful content, not just keywords
- Build topical authority clusters
- Optimize for Google's AI Overviews

**Nathan Gotch's SEO Approach:**
[Retrieved content about Search Everywhere Optimization]

- SEO = Search Everywhere Optimization now
- Target YouTube, LinkedIn, Reddit, not just Google
- Use AI to create platform-specific content variants

**Combined Strategy:**
1. Build content cluster on "AI marketing automation"
2. Create YouTube tutorials (ranks in Google + YouTube)
3. Repurpose to LinkedIn thought leadership
4. Use Reddit for community validation signals

Example 3: Community-Led Growth (Greg Isenberg)

Query:

"How do I build community around my AI productivity tool?"

Expected Response:

**Greg Isenberg's Community Framework:**

[Retrieved from NotebookLM: Community-building videos]

**Phase 1: Vibe Check (Month 1-2)**
- Find where your ideal users already hang out
- Join conversations, don't pitch
- Identify the "energy" — what gets them excited?

**Phase 2: Minimum Viable Community (Month 3)**
- Discord or Slack, not Facebook
- 1 channel: #wins (social proof flywheel)
- You post first 20 wins yourself if needed

**Phase 3: Community-Led Product**
- Ship features the community requests
- Give power users early access
- Make them feel like co-creators

**Greg's Key Insight:** "Community isn't a channel, it's a moat"

Common Patterns

Pattern 1: Multi-Stage Funnel Question

# Question spans multiple domains
"I need help with my SaaS go-to-market: offer, SEO, and community"

# Response includes:
# - Alex Hormozi: Offer positioning
# - Neil Patel: SEO strategy  
# - Greg Isenberg: Community layer

Pattern 2: Framework Deep-Dive

# Request specific framework
"Explain Alex Hormozi's Value Equation for my use case"

# Response:
# - Retrieves original explanation from NotebookLM
# - Maps framework to your specific scenario
# - Includes anti-patterns from KB

Pattern 3: Comparative Analysis

# Compare expert approaches
"How would Dan Koe vs Alex Hormozi approach pricing a course?"

# Response:
# - Dan Koe: Personal brand, premium positioning, audience relationship
# - Alex Hormozi: Value equation, enterprise pricing, sales frameworks
# - Synthesis: When to use each approach

Troubleshooting

Issue: Generic or Vague Response

Problem: Response doesn't sound like the expert

Solution:

• Check if question is in expert's domain
• Request named expert explicitly
• Ask for specific framework by name

# Instead of: "How do I market?"
# Try: "Ask Alex Hormozi: How should I position my offer using the Value Equation?"

Issue: No Retrieval Evidence

Problem: Response lacks [Retrieved from NotebookLM] markers

Solution:

• Expert may not have covered this topic
• Reframe question to match expert's known content areas
• Check expert domain table above

Issue: Multi-Expert Overload

Problem: Too many perspectives for a simple question

Solution:

• Ask for single expert
• Rephrase as focused question

# Instead of: "How do I grow?"
# Try: "What's Neil Patel's SEO strategy for [specific use case]?"

Issue: Outdated Framework

Problem: Expert's content is from 2023-2024

Solution:

• Ask for principles, not tactics
• Request ⚠️ extrapolation for 2026 context

"What would Neil Patel's SEO principles be for 2026, given AI Overviews?"

Advanced Usage

Combine with Your Context

# Provide your specific situation
"Here's my SaaS: [details]. Ask Alex Hormozi how to price it."

# Attach data
"My conversion rate is 2%. Ask Neil Patel to audit my funnel."

Sequential Expert Consultation

# Step 1: Offer with Hormozi
"Alex Hormozi: Review my offer"

# Step 2: Traffic with Neil Patel  
"Neil Patel: Now how do I drive traffic to this offer?"

# Step 3: Community with Greg Isenberg
"Greg Isenberg: Should I add a community layer?"

Export Expert Advice

# Generate structured output
"Create a marketing strategy doc consulting:
- Alex Hormozi for offer
- Neil Patel for SEO
- Greg Isenberg for community"

# Output: Markdown doc with all expert perspectives organized

Tools Used Internally

The panel is built with:

• yt-dlp: YouTube URL batch collection
• notebooklm-py: Programmatic NotebookLM access
• NotebookLM Pro: 300 sources/notebook indexing
• Claude Code Skills: Persona Protocol + dual-layer fusion

You don't need to install these separately — they're embedded in the skill.

Best Practices

1. Be specific: "How do I price?" → "How do I price a B2B SaaS at $10k ACV?"
2. Name the expert: When you know who you want
3. Provide context: Share your industry, stage, constraints
4. Request frameworks: Ask for specific models by name
5. Iterate: Start with one expert, then consult others

License

MIT — Free to use, modify, and distribute.