AI Agent Chain Workshop
Overview
Complete interactive demonstration of building intelligent AI agent workflows using classic design patterns, mimicking LangChain and LangGraph architectures.
Key Features
Chain of Responsibility Pattern: Core agent routing mechanism
SubGraph Architecture: Hierarchical agent composition (LangGraph-style)
Multi-Provider Support: Works with Gemini, OpenAI, Anthropic
Stateful Agents: Maintain context across interactions
Mock Client Testing: Test without API calls
Patterns Demonstrated
Primary Patterns
Chain of Responsibility: Agent routing and request processing
Strategy: Dynamic provider selection
Abstract Factory: Different agent type creation
Supporting Patterns
Template Method: Standardized agent workflows
Adapter: API client abstraction
Facade: Simplified system interfaces
What You'll Learn
Agent Architecture: Build modular, scalable AI systems
Request Routing: Intelligent query distribution
SubGraph Composition: Hierarchical agent organization
State Management: Context-aware conversations
Production Patterns: Error handling and resilience
Real-World Applications
Customer Support: Multi-tier agent routing
Content Systems: Research → Writing → Production workflows
Technical Support: Issue classification and escalation
Multi-Modal Processing: Text → Image → Audio pipelines
🚀 Interactive Implementation
Ready to build intelligent agent systems?
🎯 Workshop Highlights:
Live agent routing demonstrations
SubGraph architecture implementation
Real OpenAI/Gemini API integration
StateFul conversation management
Production-ready error handling
💡 Perfect For:
Understanding LangChain/LangGraph architectures
Building multi-agent AI systems
Learning enterprise AI patterns
Creating scalable agent workflows
Experience enterprise-grade agent architecture with hands-on coding and real API integration.
Last updated