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

1. Agent Architecture: Build modular, scalable AI systems

2. Request Routing: Intelligent query distribution

3. SubGraph Composition: Hierarchical agent organization

4. State Management: Context-aware conversations

5. 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

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🚀 Interactive Implementation

Ready to build intelligent agent systems?

📓 Open Interactive Notebook

🎯 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.