Agent Development - Implementation Track¶
⏱️ Estimated reading time: 3 minutes
This track provides hands-on guidance for building sophisticated agentic AI systems using LangChain and LangGraph. You'll learn to implement, optimize, and deploy production-ready AI agents. For the latest technologies like Pydantic AI, MCP, and OpenAI Swarm, see our Modern AI Frameworks track.
Table of Contents¶
| Chapter | Title | Description |
|---|---|---|
| Chapter 1 | Introduction | Overview of agentic systems and frameworks |
| Chapter 2 | LangChain | Building agent foundations |
| Chapter 3 | LangGraph | State management and workflow orchestration |
| Chapter 4 | Combined Approach | Integrated LangChain + LangGraph systems |
| Chapter 5 | DSPy | Agent optimization and prompt engineering |
| Chapter 6 | State Management | Memory and state persistence |
| Chapter 7 | Debugging | Monitoring and tracing with LangSmith |
| Chapter 8 | Unstructured Data | RAG, fine-tuning, and hybrid approaches |
| Chapter 9 | Conclusion | Best practices and deployment |
| Chapter 10 | References | Additional resources and topics |
Learning Path¶
This track is designed for hands-on learning. Start with Chapter 1 for an overview, then work through each chapter sequentially. Each chapter includes practical examples and code implementations.
Prerequisites¶
- Programming experience (Python recommended)
- Basic understanding of AI/ML concepts
- Familiarity with APIs and web services
- Completion of AI Systems track (recommended but not required)
Tools You'll Use¶
- LangChain: Agent foundation framework
- LangGraph: State management and orchestration
- DSPy: Prompt optimization and evaluation
- LangSmith: Debugging and monitoring
- Python: Primary development language
What's Next?¶
After mastering LangChain and LangGraph fundamentals, explore:
- Modern AI Frameworks: Latest 2024-2025 technologies including Pydantic AI for type-safe development, Model Context Protocol for standardized integrations, and autonomous agents like AutoGPT
- AI Systems: Theoretical foundations for deeper understanding
- AI Strategies: Strategic implementation and organizational transformation
Alternative Modern Approaches¶
While this track focuses on LangChain/LangGraph, consider these modern alternatives covered in other sections:
- Pydantic AI: For type-safe, production-ready agents with structured outputs
- OpenAI Swarm: For lightweight multi-agent coordination
- CrewAI: For role-based agent teams
- Enterprise Platforms: AWS Bedrock, Google Vertex AI, Azure AI for production deployment
Ready to start building? Begin with Chapter 1: Introduction to Agentic AI →