diff --git a/docs/examples/url_seeder/tutorial_url_seeder.md b/docs/examples/url_seeder/tutorial_url_seeder.md
index 7174b0f3..8a856784 100644
--- a/docs/examples/url_seeder/tutorial_url_seeder.md
+++ b/docs/examples/url_seeder/tutorial_url_seeder.md
@@ -1,5 +1,7 @@
 # 🔬 Building an AI Research Assistant with Crawl4AI: Smart URL Discovery
 
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1QIwVYrQaZGPJQGHQBvMSbkdnc5usqoGw#scrollTo=xbV1w9YM4LkW)
+
 ## Welcome to the Research Pipeline Workshop!
 
 In this tutorial, we'll build an **AI-powered research assistant** that intelligently discovers, filters, and analyzes web content. Instead of blindly crawling hundreds of pages, we'll use Crawl4AI's URL Seeder to:
@@ -986,6 +988,188 @@ You've built a complete AI research assistant that:
 - 📚 **Documentation**: [crawl4ai.com/docs](https://crawl4ai.com/docs)
 - 💬 **Discord**: [Join our community](https://discord.gg/crawl4ai)
 
+---
+
+## 🚀 Beyond the Basics: Advanced Agentic Patterns
+
+### The Power of Agentic Research Pipelines
+
+What you've built is just the beginning! The beauty of Crawl4AI's URL Seeder is that it enables sophisticated agentic workflows. Let's explore an advanced pattern with reflection and iterative discovery:
+
+### Advanced Pattern: Multi-Query Reflection Loop
+
+Instead of a linear pipeline, imagine an intelligent agent that:
+1. Generates multiple search strategies from your query
+2. Discovers URLs from different angles
+3. Evaluates if it has enough information
+4. Iteratively searches for missing pieces
+5. Only stops when confident in its findings
+
+Here's how this advanced flow works:
+
+```mermaid
+graph TD
+    A[🔍 User Query] --> B[🤖 Generate Multiple<br/>Search Strategies]
+    B --> C1[Query 1]
+    B --> C2[Query 2]
+    B --> C3[Query N]
+    
+    C1 --> D[🌐 Parallel URL<br/>Discovery]
+    C2 --> D
+    C3 --> D
+    
+    D --> E[🎯 Aggregate &<br/>Score All URLs]
+    E --> F[🕷️ Smart Crawling]
+    
+    F --> G{📊 Sufficient<br/>Information?}
+    G -->|No| H[🔄 Analyze Gaps]
+    H --> B
+    
+    G -->|Yes| K[🧠 AI Synthesis]
+    K --> L[📄 Comprehensive<br/>Report]
+    
+    style A fill:#e3f2fd
+    style B fill:#f3e5f5
+    style D fill:#e8f5e9
+    style G fill:#fff3e0
+    style K fill:#f3e5f5
+    style L fill:#e3f2fd
+```
+
+### Example Implementation Sketch
+
+```python
+async def advanced_research_pipeline(query: str, confidence_threshold: float = 0.8):
+    """
+    Advanced pipeline with reflection and iterative discovery
+    """
+    original_query = query
+    all_content = []
+    iteration = 0
+    max_iterations = 3
+    
+    while iteration < max_iterations:
+        # Generate multiple search strategies based on current understanding
+        search_strategies = await generate_search_strategies(
+            original_query, 
+            previous_content=all_content,
+            iteration=iteration
+        )
+        
+        # Parallel discovery from multiple angles
+        discoveries = await asyncio.gather(*[
+            discover_urls(strategy) for strategy in search_strategies
+        ])
+        
+        # Aggregate and deduplicate
+        unique_urls = aggregate_discoveries(discoveries)
+        
+        # Crawl new content
+        new_content = await crawl_selected_urls(unique_urls)
+        all_content.extend(new_content)
+        
+        # Check if we have enough information
+        confidence = await evaluate_information_completeness(
+            original_query, all_content
+        )
+        
+        if confidence >= confidence_threshold:
+            break
+            
+        # Analyze gaps to inform better queries next iteration
+        console.print(f"[yellow]Iteration {iteration + 1}: Confidence {confidence:.2f} < {confidence_threshold}[/yellow]")
+        console.print("[cyan]Generating more detailed queries based on gaps...[/cyan]")
+        
+        iteration += 1
+    
+    # Generate comprehensive synthesis
+    return await generate_final_synthesis(original_query, all_content)
+
+async def generate_search_strategies(query: str, previous_content: List = None, iteration: int = 0):
+    """Generate search strategies that get better with each iteration"""
+    
+    if iteration == 0:
+        # First iteration: broad strategies
+        prompt = f"Generate 3-5 search strategies for: {query}"
+    else:
+        # Subsequent iterations: refined based on gaps
+        gaps = analyze_content_gaps(query, previous_content)
+        prompt = f"""
+        Original query: {query}
+        
+        We've gathered some information but have gaps in:
+        {gaps}
+        
+        Generate 3-5 MORE SPECIFIC search strategies to fill these gaps.
+        """
+    
+    # Use LLM to generate strategies
+    strategies = await generate_with_llm(prompt)
+    return strategies
+```
+
+### More Agentic Patterns to Explore
+
+1. **Comparative Research Agent**
+   - Discover URLs from multiple domains
+   - Compare and contrast findings
+   - Identify consensus and disagreements
+
+2. **Fact-Checking Pipeline**
+   - Primary source discovery
+   - Cross-reference validation
+   - Confidence scoring for claims
+
+3. **Trend Analysis Agent**
+   - Time-based URL discovery
+   - Historical pattern detection
+   - Future prediction synthesis
+
+4. **Deep Dive Specialist**
+   - Start with broad discovery
+   - Identify most promising subtopics
+   - Recursive deep exploration
+
+5. **Multi-Modal Research**
+   - Discover text content
+   - Find related images/videos
+   - Synthesize across media types
+
+### Your Turn to Innovate! 🎨
+
+The URL Seeder opens up endless possibilities for intelligent web research. Here are some challenges to try:
+
+1. **Build a Research Assistant with Memory**
+   - Store previous searches
+   - Use context from past queries
+   - Build knowledge over time
+
+2. **Create a Real-Time Monitor**
+   - Periodic URL discovery
+   - Detect new content
+   - Alert on significant changes
+
+3. **Design a Competitive Intelligence Agent**
+   - Monitor multiple competitor sites
+   - Track product/feature changes
+   - Generate strategic insights
+
+4. **Implement a Learning Pipeline**
+   - Improve search strategies based on results
+   - Optimize crawling patterns
+   - Personalize to user preferences
+
+The key insight: **You're not limited to linear pipelines!** With Crawl4AI's efficient URL discovery, you can build complex agentic systems that think, reflect, and adapt.
+
+### Share Your Creations!
+
+We'd love to see what you build! Share your innovative pipelines:
+- Post in our [Discord community](https://discord.gg/crawl4ai)
+- Submit examples to our [GitHub repo](https://github.com/unclecode/crawl4ai)
+- Tag us on social media with #Crawl4AI
+
+Remember: The best AI agents are those that augment human intelligence, not replace it. Build tools that help you think better, research faster, and discover insights you might have missed.
+
 Thank you for learning with Crawl4AI! 🙏
 
 Happy researching! 🚀🔬
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