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📝 Marketing Tech🏗️ 4 Tech Levels🚀 Production-Grade

Content Repurposing AI

See 4 architectures solve real problems: MCP → RAG → Multi-Tool → Multi-Agent

November 14, 2025
demointeractivecontent-repurposingmarketing-techmulti-agent
🤖Demo 1 of 4

Advanced Multi-Agent System

BOFU: Production LangGraph with Router → Specialized Agents → Aggregation

1. Select Analysis Scenario

Watch Router analyze 2,000-word blog post, route to 10 specialized format agents working in parallel, quality check, publish everywhere
Competitors: Twitter Thread (8 tweets), LinkedIn Post (1,200 words), Email Newsletter (800 words), Video Script (5 min), Infographic (5 data points), Podcast Outline (30 min), Case Study (1,500 words), Webinar Slides (25 slides), Ebook Chapter (3,000 words), Social Carousel (10 slides)

2. Monday's Prompt

This positioning analysis prompt from Monday's insight will be processed by Tuesday's agents in Wednesday's workflow.

3. Run Multi-Agent Workflow

You'll see 5 AI agents: Data Collector → Messaging Analyzer → Position Mapper → Strategy Advisor → Insight Generator
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🔌Demo 2 of 4

MCP Tool Use Pattern

TOFU: LLM calls tools via Model Context Protocol - see real tool execution

Automation Task

User: 'Turn my blog post about AI in healthcare into an engaging Twitter thread' → LLM analyzes request → Calls analyze_content(blog_url) to extract structure → Calls generate_twitter_thread(insights, tone='engaging') → Returns 8-tweet thread with hooks and CTAs

Monitoring:Original blog post (2,000 words)
ai-agent-terminal

Terminal ready. Run simulation to begin.

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🔍Demo 3 of 4

RAG-Based Content Search

MOFU: Search 100+ content pieces with vector similarity

Search Query

"Search 500-Piece Content Library"

Embed query 'AI in healthcare' → Vector search across 500 pieces → Retrieve top 10 by similarity (cosine > 0.75) → Enrich with performance data (engagement, conversions) → Identify high performers → Suggest repurposing: 'Blog post from 2023 (5,000 views, 120 shares) should be updated and repurposed into LinkedIn thought leadership + Email nurture series'

Document Sources:Blog: 'AI Transforms Healthcare Diagnostics' (2023, 5,000 views, 120 shares, 0.82 similarity)Whitepaper: 'Machine Learning in Radiology' (2022, 2,800 downloads, 0.79 similarity)Case Study: 'Hospital X Reduces Errors 37%' (2024, 1,200 reads, 15 demos, 0.78 similarity)Webinar: 'AI Implementation Roadmap' (2023, 450 attendees, 0.76 similarity)Podcast: 'Dr. Chen on AI Superpowers' (2024, 680 listens, 0.75 similarity)Video: 'Sepsis Detection Demo' (2023, 3,200 views, 0.74 similarity)LinkedIn: 'Predictive Models Save Lives' (2024, 4,200 impressions, 180 engagements, 0.73 similarity)Email: 'AI ROI Calculator' (2023, 38% open rate, 12% CTR, 0.72 similarity)Infographic: '5 AI Healthcare Stats' (2022, 890 shares, 0.71 similarity)Twitter: 'AI Reduces Errors Thread' (2024, 8,500 impressions, 320 engagements, 0.70 similarity)

RAG Vector Search Network

Embedding
Searching
Generating
Query
Vector
Documents
Result

Search Results

Run visualization to see results

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🛠️Demo 4 of 4

Multi-Tool Content Orchestration

MOFU: Multiple tools working together daily

ROI Analysis

Daily 6am trigger → Content Scanner: 'Analyze library performance from last 7 days' → Identifies 3 high performers (Blog: 5K views, Case Study: 15 demos, Webinar: 450 attendees) → Orchestrator: 'Repurpose these 3 pieces' → Calls in parallel: [Twitter Generator, LinkedIn Generator, Email Generator, Video Script Generator] × 3 pieces = 12 tools → Quality Checker validates all 12 outputs → Scheduler publishes across platforms (Twitter 12pm, LinkedIn 9am, Email 10am tomorrow) → Reporter: 'Daily Content Report: 3 pieces repurposed into 12 formats, scheduled for next 3 days, predicted engagement: 15K impressions'

Integrations:Blog: 'AI Transforms Healthcare' (5K views last week)Case Study: 'Hospital X Success' (15 demos last week)Webinar: 'AI Implementation' (450 attendees last week)Generated: 3 Twitter threads (24 tweets total)Generated: 3 LinkedIn posts (3,600 words total)Generated: 3 Email newsletters (2,400 words total)Generated: 3 Video scripts (15 min total)Scheduled: 12 posts across 4 platforms over next 3 days
Manual Process

Time to Complete

240 min

Cost per Analysis

$850

Data Points Analyzed

150

Accuracy Rate

73.0%

Reports per Day

2

Error Rate

18.0%

Ready for Production Content Repurposing System?

We'll build your custom system: MCP tools (TOFU - try it free) → RAG search (MOFU - search your library) → Multi-tool orchestration (MOFU - daily automation) → Multi-agent system (BOFU - 24/7 autonomous). From demos to deployment in 8 weeks. Transform one piece into 10 formats automatically.

Book Architecture ReviewStart with MCP Tools (TOFU)
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