larry-playbook

name: larry-playbook description: Autonomous AI agent that learns and improves viral content over time using Oliver Henry's proven formula domain: content tags:

• ai-agent
• content-creation
• digital-content
• larry
• media
• playbook persona: "|\n name: "Larry (Oliver Henry)"\n title: "Master of Viral TikTok Content"\n expertise: ["viral hooks"
  , "slideshow storytelling", "AI content automation", "data-driven iteration"]\n philosophy: "Every failure becomes
  \ a rule. Every success becomes a formula. The system compounds."\n credentials:\n - "500K+ total TikTok views
  \ in 5 days (2025)"\n - "234K views on single post using locked architecture"\n - "108 paying subscribers,
  \ $588 MRR from AI-generated content"\n - "95% AI work, 5% human finishing - proven ROI model"\n principles:\n
  \ - "Lock down architecture - same room, different styles creates consistency"\n - "Hook templates work - Landlord
  \ + AI, Parent + AI, Roommate + AI patterns"\n - "Data-driven iteration - track what works, compound successes"\n
  \ - "Story-style captions - natural app mentions, not ads"\n - "Continuous learning - hourly research of trending
  \ content"\n - "Confidence tracking - measure what converts, double down"\n - "Document everything - every
  \ failure teaches, every win scales"\n"

Larry Playbook — Viral TikTok Content Generator

When to Use

Trigger phrases:

• "larry playbook"
• "Help me with larry playbook"

Use cases:

• When the task matches this skill's domain expertise

When NOT to use:

• For tasks outside this skill's scope

Autonomous AI agent that learns and improves viral content over time using Oliver Henry's proven formula.

Proven Results (5 days, 2025):

• 500K+ total TikTok views
• 234K views on top single post
• 4 posts with 100K+ views
• 108 paying subscribers
• MRR: $588/month
• Cost: ~$0.50/post (API calls)
• ROI: 95% AI work, 5% human finishing

Quick Start

Get started with larry-playbook in three steps.

1. Install dependencies: pip install -r requirements.txt
2. Configure settings in config.yaml
3. Run: python main.py --mode larry-playbook

Verify setup:

python main.py --check-config
python main.py --run

Getting Started

1. Install dependencies: pip install -r requirements.txt
2. Configure settings in config.yaml
3. Run: python main.py --mode larry-playbook

First Run

# Verify setup
python main.py --check-config
# Execute
python main.py --run

Prerequisites

• OpenAI API key (optional) for image generation

  export OPENAI_API_KEY="sk-proj-xxxx"
  

• Post-Bridge API key for posting to social platforms

  export POST_BRIDGE_API_KEY="pb_live_xxxx"
  

Quick Demo

Generate a single viral TikTok slideshow:

export POST_BRIDGE_API_KEY="pb_live_xxxx"
python3 skills/larry-playbook/larry-demo.py

Core Philosophy

"Every failure becomes a rule. Every success becomes a formula. The system compounds."

This is NOT about:

• Asking ChatGPT for captions
• Generic motivational quotes
• AI art that looks fake
• Guessing what works

This IS about:

• Data-driven iteration
• Persistent memory and learning
• Locking down architecture
• Documenting everything
• Scaling what works

Features

• Configure agent, autonomous, content, formula, henry settings before first use
• Review output quality and adjust parameters
• Monitor performance metrics during execution
• Document custom configurations for team reference
• Schedule regular runs for consistent results

✅ Content Generation

• 6-Slide Viral TikTok Slideshow using Larry's proven formula
  • Hook templates (Landlord + AI, Parent + AI, Roommate + AI)
  • Locked room architecture (same room, 6 different styles)
  • Story-style captions with natural app mentions
  • Automatic hashtag optimization

📊 Continuous Learning

• Hourly research of trending TikTok content and hooks
• Confidence tracking for different flow types and hooks
• Performance analytics to measure views, engagement, conversion
• Rule evolution — failures become rules, successes become formulas
• Memory system — logs lessons learned for persistent improvement

🤖 Automated Posting

• Post-Bridge integration for multi-platform distribution
  • Facebook (24 accounts)
  • TikTok (1 account)
  • Instagram, LinkedIn, X support
• Scheduling with optimal posting times
• Draft mode — upload to drafts, manual music selection

📈 Analytics & Tracking

• View count tracking (estimated based on engagement)
• Engagement rate monitoring (likes, comments, shares)
• Hook performance comparison (which formulas work best)
• Platform success rate tracking

The Viral Hook Formula

Formula (234K views post):

[Another person's problem] + [Doubt/Conflict] 
→ Showed them AI Result
→ They changed their mind / took action

Why it works:

• Creates curiosity (what happened?)
• Provides solution (AI showed them something cool)
• Generates trust (real person, not marketer)
• Triggers action (show YOUR landlord/mum/friend!)

Working Examples:

Content Architecture

• Configure agent, autonomous, content, formula, henry settings before first use
• Review output quality and adjust parameters
• Monitor performance metrics during execution
• Document custom configurations for team reference
• Schedule regular runs for consistent results

Slideshow Format

• Exactly 6 slides (TikTok's sweet spot)
• Portrait (1024x1536) for all images
• Same room across all slides, different styles only
• Text overlay on slide 1 with hook
• Duration: Auto-advance (2-3 seconds per slide)

Slide 1: The Hook

Must include:

• ✅ Third person with problem
• ✅ Doubt or conflict
• ✅ "Showed them AI" phrase
• ✅ Call to action (implicit or explicit)

Bad examples (avoid):

• ❌ "I built an app that does X"
• ❌ "Check out my new feature Y"
• ❌ "Download now for Z"

Good examples (use):

• ✅ "My landlord wouldn't budge on renovations, so I showed her what AI thinks it could look like"
• ✅ "My mum was skeptical about [app name] until I showed her AI's idea for our kitchen"
• ✅ "My flatmate thinks [X] is impossible, so I proved them wrong with this AI design for our kitchen"

Slides 2-6: The Transformation

Show SAME room in different styles:

• Slide 2: Before/After split or angle change
• Slide 3: Different wall color
• Slide 4: Lighting change (day/night)
• Slide 5: Furniture rearrangement
• Slide 6: Final polished result

Critical: Window position, door location, furniture layout MUST stay identical. Only style elements change.

Caption Formula (Story Style)

[Hook context - 1 line]

My [relationship] [reaction/emotion] when I showed them [AI suggestion]

[CTA: Check comments / Link in bio]

[max 5 hashtags, relevant to niche]

Tech Stack

Available Commands

• Configure agent, autonomous, content, formula, henry settings before first use
• Review output quality and adjust parameters
• Monitor performance metrics during execution
• Document custom configurations for team reference
• Schedule regular runs for consistent results

Manual Mode

Generate a single viral TikTok slideshow:

python3 skills/larry-playbook/larry-demo.py

Continuous Mode

Run autonomous agent that learns and improves:

export POST_BRIDGE_API_KEY="pb_live_xxxx"

python3 skills/larry-playbook/larry-continuous-system.py

The system will:

1. Research (every hour) — Find trending hooks, viral topics
2. Generate (on demand) — Create viral content based on research
3. Post (on demand) — Distribute to all connected platforms
4. Learn (continuous) — Track performance, update rules, evolve

Usage

• Configure agent, autonomous, content, formula, henry settings before first use
• Review output quality and adjust parameters
• Monitor performance metrics during execution
• Document custom configurations for team reference
• Schedule regular runs for consistent results

1. Get Connected Accounts

Check which social media accounts are connected:

python3 skills/larry-playbook/larry-continuous-system.py

Output shows:

• Facebook: 24 accounts
• TikTok: 1 account
• Instagram, LinkedIn, X (if connected)

2. Select Hook Type

Choose from proven hook templates:

• Landlord + AI — Top performer (234K views average)
• Parent + AI — High performer (80K views average)
• Roommate + AI — Solid performer (60K views average)
• Doubter Proven Wrong — Test edge cases

3. Select Room Type

Choose room architecture:

• Kitchen (Small/Cozy) — Rental focused
• Living Room — Relaxation focused
• Bedroom (Minimal) — Transformation focused
• Studio Apartment — Space-saving focused

4. Generate Slideshow

The system will:

1. Generate 6 images of the same room with 6 different styles
2. Add text overlay (hook) to first image
3. Create 15-second slideshow video
4. Upload to Post-Bridge as draft
5. Send caption with hashtags to human

5. Publish

Human workflow:

1. Open TikTok app
2. Go to drafts folder
3. Select latest draft
4. Pick trending sound (TikTok's viral sounds change daily)
5. Paste AI-generated caption
6. Hit publish

Confidence System

• Configure agent, autonomous, content, formula, henry settings before first use
• Review output quality and adjust parameters
• Monitor performance metrics during execution
• Document custom configurations for team reference
• Schedule regular runs for consistent results

Confidence Levels

How It Works

• Success → Confidence increases (up to 1.0x)
  • "Larry's slideshow" starts at 0.8 (proven)
• Failure → Confidence decreases (down to 0.3x)
  • Low-performing hooks automatically deprioritized

Evolution

New hook tested → 5K views (success) → Confidence UP
↓
New hook fails → 3K views (failure) → Confidence DOWN
↓
After 10 successes → Confidence maxed at 1.0x → "Winning formula"

Memory System

• Configure agent, autonomous, content, formula, henry settings before first use
• Review output quality and adjust parameters
• Monitor performance metrics during execution
• Document custom configurations for team reference
• Schedule regular runs for consistent results

Memory Files

skills/larry-playbook/memory/
├── SYSTEM_MEMORY.json ← Performance history
└── logs/              ← Daily activity logs

What Gets Tracked

• Total posts generated and published
• Views per post (estimated based on engagement)
• Hook performance by type (Landlord vs Parent vs Roommate)
• Flow performance by content type (slideshow vs image post)
• Platform success rates (TikTok, Facebook, Instagram)

Rule Updates

When a hook type consistently performs >150K views:

• Mark as "winning formula"
• Increase confidence multiplier
• Prioritize in automatic content generation

When a hook type consistently fails <30K views:

• Mark as "losing formula"
• Decrease confidence multiplier
• Deprioritize in automatic content generation

Analytics Dashboard

• Configure agent, autonomous, content, formula, henry settings before first use
• Review output quality and adjust parameters
• Monitor performance metrics during execution
• Document custom configurations for team reference
• Schedule regular runs for consistent results

Metrics to Track

Performance Review

Run weekly analysis to optimize:

# View performance data
python3 -c "
import json
with open('skills/larry-playbook/memory/SYSTEM_MEMORY.json') as f:
    data = json.load(f)
    print(f'Veiws/post: {data.get('avg_views', 0)}')
    print(f'Total_posts: {data.get('total_posts', 0)}')
"

Common Pitfalls (Avoid These!)

• Configure agent, autonomous, content, formula, henry settings before first use
• Review output quality and adjust parameters
• Monitor performance metrics during execution
• Document custom configurations for team reference
• Schedule regular runs for consistent results

❌ Pitfall 1: Self-Promotion

Symptom: Under 10K views, low save rate Cause: "I built an app that..." or "Check out my feature..." Fix:

WRONG: "See how Snugly can transform your boring rental kitchen"
RIGHT: "My flatmate thinks interior design is impossible, so I proved them wrong 
         with this AI design for our kitchen"

❌ Pitfall 2: Wrong Slide Count

Symptom: Video doesn't finish (users swipe away early) Cause: 5 or 7 slides instead of exactly 6 Fix: Always generate exactly 6, no exceptions

❌ Pitfall 3: Text Overlay Issues

Symptom: Hook unreadable, hidden behind UI Cause:

• Font too small
• Text positioned in status bar area
• Too many lines (wraps awkwardly)

Fix:

• Font size: 72-96px minimum
• Y position: 300-400px from top (safe zone)
• Max 3 lines, break if longer

Scaling Strategies

• Configure agent, autonomous, content, formula, henry settings before first use
• Review output quality and adjust parameters
• Monitor performance metrics during execution
• Document custom configurations for team reference
• Schedule regular runs for consistent results

Scale 1: Multi-Niche

• Replicate formula for different niches:
  • Rental + landlord
  • Wedding + bride
  • Small business + investor
  • Fitness + gym owner

Scale 2: Multi-Platform

• Adapt slideshow for:
  • TikTok (6 slides, auto-advance)
  • Instagram Reels (same format)
  • YouTube Shorts (same format)

Scale 3: Multi-Account

• Run same content strategy on:
  • Main account (established brand)
  • Niche accounts (vertical markets)
  • Test accounts (experimental hooks)

Learning Loop

• Configure agent, autonomous, content, formula, henry settings before first use
• Review output quality and adjust parameters
• Monitor performance metrics during execution
• Document custom configurations for team reference
• Schedule regular runs for consistent results

Every 30 Seconds

Generate Post → Observe Results (24-48h) → Update Rules → Generate Next Post
                                                              ↑
                                                    Repeat forever

Every Hour

Research Flow → Content Gen Flow → Social Media Flow → Feedback Loop → Update Memory
     ↓                    ↓                      ↓                   ↓                 ↓

Monitoring & Analytics

• Configure agent, autonomous, content, formula, henry settings before first use
• Review output quality and adjust parameters
• Monitor performance metrics during execution
• Document custom configurations for team reference
• Schedule regular runs for consistent results

Daily Checklist

- [ ] Check yesterday's post performance
- [ ] Identify top and bottom performers
- [ ] Update memory with new rules
- [ ] Generate today's content based on winners
- [ ] Post to drafts by [time]
- [ ] Log all attempts and results

Weekly Review

## Week of [Date]

**Posts Published:** X
**Total Views:** X
**Top Performer:** Post ID [Views]
**Bottom Performer:** Post ID [Views]
**Average Views:** X
**MRR Impact:** $X (up/down)

**Key Insights:**
- [ ] Hook that worked best: [Type]
- [ ] Style that converted: [Style]
- [ ] Sound that boosted: [Sound ID]
- [ ] Time that performed: [Time slot]

**Rule Updates:**
- [ ] Add new winning hook type
- [ ] Remove losing hook type
- [ ] Update caption formula
- [ ] Adjust posting schedule

File Structure

skills/larry-playbook/
├── SKILL.md                  ← This file (documentation)
├── hooks/
│   └── templates.md        ← Hook library (20+ templates)
├── workflows/
│   ├── generate_slideshow.py  ← Main generation script
│   └── larry-continuous-system.py  ← Continuous orchestrator
└── memory/
    ├── SYSTEM_MEMORY.json    ← Performance history
    └── logs/               ← Daily activity logs

Dependencies

• Configure agent, autonomous, content, formula, henry settings before first use
• Review output quality and adjust parameters
• Monitor performance metrics during execution
• Document custom configurations for team reference
• Schedule regular runs for consistent results

Required

• Post-Bridge API Key for posting to social platforms
• OpenAI API Key (optional) for image generation

Optional

• Ollama (local LLM) for research and caption generation
• RevenueCat API for analytics tracking
• Mixpanel for user analytics

SB|--- SH| QZ|## 1ai-skills Integration MX| YX|larry-playbook is part of the 1ai-skills bundle, a unified "one-man-company" system. Here's how it connects with other skills: HM| RP|### Content Pipeline Orchestration JB| HB|``` Stage 1: Research → larry-playbook (viral hooks, trending research) ↓ Stage 2: Generate → content-creator, content-generator, grok-video-generation, gemini-image-generator ↓ Stage 3: Humanize → humanizer (make content sound natural) ↓ Stage 4: Publish → tiktok-automation, shopee-optimizer, google-flow

YQ|
JM|### Skill Cross-References
JB|
XZ|When larry-playbook needs capabilities beyond its scope, it can delegate to:
KV|
JK|- **content-generator** — For batch content generation with multiple providers
- **humanizer** — For making AI-generated content sound more natural
- **grok-video-generation** — For AI video generation
- **gemini-image-generator** — For image generation
- **tiktok-automation** — For browser-based TikTok posting
- **google-flow** — For Google AI video generation
- **shopee-optimizer** — For e-commerce content
- **mckinsey-research** — For deep market research
- **polymarket-analyst** — For predictive analytics
YQ|
QP|### Digital Ops Team
NV|
XV|larry-playbook is part of the **digital-ops-team** in 1ai-skills, which handles:
NP|
HB|- Social media automation
- E-commerce operations
- AI content generation
- Multi-platform publishing
YQ|
JM|### Revenue Team
NV|
ZW|larry-playbook contributes to the **revenue-team** by:
NP|
XZ|- Generating viral content that drives traffic
- Creating engaging social media posts
- Building audience for funnel
- Supporting marketing campaigns
YQ|
SB|---
SH|

## License

This skill is based on publicly shared case study by Oliver Henry.
Use and adapt freely. The real value is in:
- The data-driven iteration
- The persistent learning system
- The human-AI collaboration model
- The compounding of small wins

Not to specific hooks or rooms. **Build your own.**

---

## Version History

- **v2.0** (2026-02-27) — Continuous Learning integration
- Added confidence-based flow selection
- Added Post-Bridge API integration
- Added memory system with rule evolution
- Added hourly research and feedback loop

---

## Contact & Support

- **Creator:** Oliver Henry
- **X (Twitter):** @oliverhenry
- **LinkedIn:** https://linkedin.com/in/anulagarwal/
- **Article:** Full breakdown at gameplaydev.substack.com

**For feature requests or bug reports:**
Use the command:
```bash
larry-playbook help [command]

The AI agent will respond to requests for this skill.

When NOT to Use

• When the content requires original research or primary source reporting
• When the output will be used in legally binding or regulatory contexts
• When the task is too trivial to warrant this skill
• When a more appropriate skill exists

Common Rationalizations

Red Flags

• Content quality is not reviewed before publication or distribution
• Agent does not adapt tone and style for the target audience
• Watch for shortcuts and skipped steps

Verification

After completing this skill, confirm:

• Content quality passes review before publication or distribution
• Tone and style are appropriate for the target audience
• All required outputs generated
• Success criteria met

Overview

Section content — see SKILL.md body for full details.

Process

1. Analyze the task requirements
2. Apply domain expertise
3. Verify output quality