Summary
In this chapter, you learned about the essential components and techniques for designing effective agentic systems. We explored how focused system prompts guide agent behavior, how state space representations and environment models create a foundation for decision-making, and how different memory architectures – short-term, long-term, and episodic – work together with context management to enable coherent interactions and learning from past experiences.
Through our travel agent example, we demonstrated how the integration of sequential and parallel processing patterns, supported by intelligent workflow optimization strategies, enables agents to handle complex tasks efficiently while maintaining system reliability. These design techniques work together to create systems that can effectively manage real-world scenarios, adapt to changing conditions, and provide consistent, high-quality service to users. By implementing these practices thoughtfully, developers...
