Orchestrating Language Model Agents: Technical Approaches to Scalable Application Development for Experienced Practitioners: 3 (The Professional AI Agent Systems Engineering Series) - Softcover
Book 3 of 3: The Professional AI Agent Systems Engineering Series
Synopsis
This book examines technical methods for designing and implementing systems that coordinate language model agents to support complex, production-grade applications. It addresses core architectural patterns, coordination mechanisms, state management, tool integration, and scalability considerations in multi-agent environments powered by large language models. Drawing from established frameworks such as LangGraph, AutoGen, and CrewAI, along with advanced concepts in agent collaboration, planning, memory persistence, and workflow control, the content focuses on practical engineering decisions required for reliable deployment at scale.
The material assumes familiarity with large language models, prompt engineering, Python development, and basic AI system design. It is intended for software engineers, AI architects, and technical leads building enterprise-grade agentic systems, rather than introductory learners.
Explore these structured approaches to enhance the robustness and efficiency of your LLM-based applications. Add this resource to your library today for detailed reference in professional development projects.
"synopsis" may belong to another edition of this title.
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Orchestrating Language Model Agents: Technical Approaches to Scalable Application Development for Experienced Practitioners (The Professional AI Agent Systems Engineering Series)
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Paperback. Condition: new. Paperback. This book examines technical methods for designing and implementing systems that coordinate language model agents to support complex, production-grade applications. It addresses core architectural patterns, coordination mechanisms, state management, tool integration, and scalability considerations in multi-agent environments powered by large language models. Drawing from established frameworks such as LangGraph, AutoGen, and CrewAI, along with advanced concepts in agent collaboration, planning, memory persistence, and workflow control, the content focuses on practical engineering decisions required for reliable deployment at scale. The material assumes familiarity with large language models, prompt engineering, Python development, and basic AI system design. It is intended for software engineers, AI architects, and technical leads building enterprise-grade agentic systems, rather than introductory learners. Explore these structured approaches to enhance the robustness and efficiency of your LLM-based applications. Add this resource to your library today for detailed reference in professional development projects. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798248571475
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