1. Introduction to Agents -- 2. Designing agent systems -- 3. User experience design for agentic systems -- 4. Tool use -- 5. Orchestration -- 6. Knowledge and memory -- 7. Learning in agentic systems -- 8. From one Agent to many -- 9. Validation and measurement -- 10. Monitoring in production -- 11. Improvement loops -- 12. Protecting agentic systems -- 13. Human-agent collaboration

Generative AI has revolutionized how organizations tackle problems, accelerating the journey from concept to prototype to solution. As the models become increasingly capable, we have witnessed a new design pattern emerge : AI agents. By combining tools, knowledge, memory, and learning with advanced foundation models, we can now sequence multiple model inferences together to solve ambiguous and difficult problems. From coding agents to research agents to analyst agents and more, we've already seen agents accelerate teams and organizations. While these agents enhance efficiency, they often require extensive planning, drafting, and revising to complete complex tasks, and deploying them remains a challenge for many organizations, especially as technology and research rapidly develops. This book is your indispensable guide through this intricate and fast-moving landscape. Author Michael Albada provides a practical and research-based approach to designing and implementing single- and multiagent systems. It simplifies the complexities and equips you with the tools to move from concept to solution efficiently. -- Provided by publisher