Isbn: 9798263798017 - agentic ai in action: building autonomous multi-agent systems for real-world applications: practical workflows, advanced orchestration, and scalable ... 1 (ai projects and workflow systems series) (11 resultados)

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PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Condición: New.

Condición: As New. Unread book in perfect condition.

Paperback. Condición: New.

Paperback. Condición: new. Paperback. A rigorous, project-driven engineering guide to designing, implementing, and operating autonomous multi-agent systems. This book moves beyond theory to deliver production-grade patterns, tested code examples, and deployment strategies that enable teams to build resilient, observable, and secure agentic AI solutions.What's insideConcise theoretical foundations for agentic AI and multi-agent coordination.Architectural patterns for agent communication, role assignment, and decision policies.End-to-end Python implementations and reproducible projects (business automation, conversational agents, orchestrated pipelines).Engineering concerns: state management, retries, fault tolerance, monitoring, logging, and observability.Integration strategies for external APIs, databases, and vector stores.Security, compliance, and production hardening guidance.Key topics;agentic AI, multi-agent systems, autonomous agents, orchestration, workflow automation, agent communication, decision policies, fault tolerance, observability, Python, API integration, production scaling.Who should read thisSoftware engineers, ML engineers, platform architects, and technical leads building multi-step LLM workflows or autonomous pipelines that must operate reliably in production. Prior experience with Python and basic ML/LLM concepts is recommended.Deliverables & formatPractical code examples and templates ready for integration into production codebases.Two complete case studies with architecture diagrams and operational checklists.Best-practice playbooks for testing, deployment, incident response, and scaling. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Condición: New. Print on Demand.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Paperback. Condición: new. Paperback. A rigorous, project-driven engineering guide to designing, implementing, and operating autonomous multi-agent systems. This book moves beyond theory to deliver production-grade patterns, tested code examples, and deployment strategies that enable teams to build resilient, observable, and secure agentic AI solutions.What's insideConcise theoretical foundations for agentic AI and multi-agent coordination.Architectural patterns for agent communication, role assignment, and decision policies.End-to-end Python implementations and reproducible projects (business automation, conversational agents, orchestrated pipelines).Engineering concerns: state management, retries, fault tolerance, monitoring, logging, and observability.Integration strategies for external APIs, databases, and vector stores.Security, compliance, and production hardening guidance.Key topics;agentic AI, multi-agent systems, autonomous agents, orchestration, workflow automation, agent communication, decision policies, fault tolerance, observability, Python, API integration, production scaling.Who should read thisSoftware engineers, ML engineers, platform architects, and technical leads building multi-step LLM workflows or autonomous pipelines that must operate reliably in production. Prior experience with Python and basic ML/LLM concepts is recommended.Deliverables & formatPractical code examples and templates ready for integration into production codebases.Two complete case studies with architecture diagrams and operational checklists.Best-practice playbooks for testing, deployment, incident response, and scaling. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…