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Agentic Systems in Production: Practical Approaches to Multi-Agent Orchestration and Reliability at Scale for Experienced Engineers - Softcover
Synopsis
This book examines the engineering challenges and architectural patterns required to deploy agentic AI systems in production environments. It addresses multi-agent orchestration, system reliability, observability, governance, and scaling considerations that arise when moving beyond experimental prototypes to enterprise-grade deployments.
Drawing on current practices in distributed systems, workflow coordination, failure recovery, and performance management, the content focuses on technical implementations suitable for professionals already familiar with AI development, large language models, and production infrastructure. Topics include agent specialization, coordination mechanisms, cost control, observability pipelines, and integration with existing enterprise stacks.
The material assumes working knowledge of AI frameworks, cloud operations, and software engineering principles. It is intended for AI engineers, machine learning practitioners, and technical leads responsible for building and maintaining reliable agentic applications at scale in 2026 and beyond.
If you are an experienced professional seeking detailed, practical insights into productionizing multi-agent systems, this reference provides structured analysis of the relevant engineering approaches.
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Agentic Systems in Production (Paperback)
Print on DemandSeller: Grand Eagle Retail, Bensenville, IL, U.S.A.
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Paperback. Condition: new. Paperback. This book examines the engineering challenges and architectural patterns required to deploy agentic AI systems in production environments. It addresses multi-agent orchestration, system reliability, observability, governance, and scaling considerations that arise when moving beyond experimental prototypes to enterprise-grade deployments. Drawing on current practices in distributed systems, workflow coordination, failure recovery, and performance management, the content focuses on technical implementations suitable for professionals already familiar with AI development, large language models, and production infrastructure. Topics include agent specialization, coordination mechanisms, cost control, observability pipelines, and integration with existing enterprise stacks. The material assumes working knowledge of AI frameworks, cloud operations, and software engineering principles. It is intended for AI engineers, machine learning practitioners, and technical leads responsible for building and maintaining reliable agentic applications at scale in 2026 and beyond. If you are an experienced professional seeking detailed, practical insights into productionizing multi-agent systems, this reference provides structured analysis of the relevant engineering approaches. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9798254671923
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Agentic Systems in Production: Practical Approaches to Multi-Agent Orchestration and Reliability at Scale for Experienced Engineers
Print on DemandSeller: California Books, Miami, FL, U.S.A.
Seller rating 4 out of 5 stars
Condition: New. Print on Demand. Seller Inventory # I-9798254671923
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Agentic Systems in Production (Paperback)
Print on DemandSeller: CitiRetail, Stevenage, United Kingdom
Seller rating 5 out of 5 stars
Paperback. Condition: new. Paperback. This book examines the engineering challenges and architectural patterns required to deploy agentic AI systems in production environments. It addresses multi-agent orchestration, system reliability, observability, governance, and scaling considerations that arise when moving beyond experimental prototypes to enterprise-grade deployments. Drawing on current practices in distributed systems, workflow coordination, failure recovery, and performance management, the content focuses on technical implementations suitable for professionals already familiar with AI development, large language models, and production infrastructure. Topics include agent specialization, coordination mechanisms, cost control, observability pipelines, and integration with existing enterprise stacks. The material assumes working knowledge of AI frameworks, cloud operations, and software engineering principles. It is intended for AI engineers, machine learning practitioners, and technical leads responsible for building and maintaining reliable agentic applications at scale in 2026 and beyond. If you are an experienced professional seeking detailed, practical insights into productionizing multi-agent systems, this reference provides structured analysis of the relevant engineering approaches. 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 # 9798254671923
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