Isbn: 9781806690053 - context engineering for multi-agent systems: move beyond prompting to build a context engine, a transparent architecture of context and reasoning (22 resultados)

Condición: good. Has a sturdy binding with some shelf wear. May have some markings or highlighting. Used copies may not include access codes or Cd's. Slight bending may be present.

paperback. Condición: Very Good. Cover and edges may have some wear.

Paperback or Softback. Condición: New. Context Engineering for Multi-Agent Systems: Move beyond prompting to build a Context Engine, a transparent architecture of context and reasoning. Book.

Condición: New.

Paperback. Condición: New. Build AI that thinks in context using semantic blueprints, multi-agent orchestration, memory, RAG pipelines, and safeguards to create your own Context EngineFree with your book: DRM-free PDF version + access to Packt's next-gen Reader*Key FeaturesDesign semantic blueprints to give AI structured, goal-driven contextual awarenessOrchestrate multi-agent workflows with MCP for adaptable, context-rich reasoningEngineer a glass-box Context Engine with high-fidelity RAG, trust, and safeguardsBook DescriptionGenerative AI is powerful, yet often unpredictable. This guide shows you how to turn that unpredictability into reliability by thinking beyond prompts and approaching AI like an architect. At its core is the Context Engine, a glass-box, multi-agent system you'll learn to design and apply across real-world scenarios.Written by an AI guru and author of various cutting-edge AI books, this book takes you on a hands-on journey from the foundations of context design to building a fully operational Context Engine. Instead of relying on brittle prompts that give only simple instructions, you'll begin with semantic blueprints that map goals and roles with precision, then orchestrate specialized agents using the Model Context Protocol. As the engine evolves, you'll integrate memory and high-fidelity retrieval with citations, implement safeguards against data poisoning and prompt injection, and enforce moderation to keep outputs aligned with policy. You'll also harden the system into a resilient architecture, then see it pivot across domains, from legal compliance to strategic marketing, proving its domain independence.By the end of this book, you'll be equipped with the skills to engineer an adaptable, verifiable architecture you can repurpose across domains and deploy with confidence.*Email sign-up and proof of purchase requiredWhat you will learnDevelop memory models to retain short-term and cross-session contextCraft semantic blueprints and drive multi-agent orchestration with MCPImplement high-fidelity RAG pipelines with verifiable citationsApply safeguards against prompt injection and data poisoningEnforce moderation and policy-driven control in AI workflowsRepurpose the Context Engine across legal, marketing, and beyondDeploy a scalable, observable Context Engine in productionWho this book is forThis book is for AI engineers, software developers, system architects, and data scientists who want to move beyond ad hoc prompting and learn how to design structured, transparent, and context-aware AI systems. It will also appeal to ML engineers and solutions architects with basic familiarity with LLMs who are eager to understand how to orchestrate agents, integrate memory and retrieval, and enforce safeguards.…

Paperback. Condición: New. Build AI that thinks in context using semantic blueprints, multi-agent orchestration, memory, RAG pipelines, and safeguards to create your own Context EngineFree with your book: DRM-free PDF version + access to Packt's next-gen Reader*Key FeaturesDesign semantic blueprints to give AI structured, goal-driven contextual awarenessOrchestrate multi-agent workflows with MCP for adaptable, context-rich reasoningEngineer a glass-box Context Engine with high-fidelity RAG, trust, and safeguardsBook DescriptionGenerative AI is powerful, yet often unpredictable. This guide shows you how to turn that unpredictability into reliability by thinking beyond prompts and approaching AI like an architect. At its core is the Context Engine, a glass-box, multi-agent system you'll learn to design and apply across real-world scenarios.Written by an AI guru and author of various cutting-edge AI books, this book takes you on a hands-on journey from the foundations of context design to building a fully operational Context Engine. Instead of relying on brittle prompts that give only simple instructions, you'll begin with semantic blueprints that map goals and roles with precision, then orchestrate specialized agents using the Model Context Protocol. As the engine evolves, you'll integrate memory and high-fidelity retrieval with citations, implement safeguards against data poisoning and prompt injection, and enforce moderation to keep outputs aligned with policy. You'll also harden the system into a resilient architecture, then see it pivot across domains, from legal compliance to strategic marketing, proving its domain independence.By the end of this book, you'll be equipped with the skills to engineer an adaptable, verifiable architecture you can repurpose across domains and deploy with confidence.*Email sign-up and proof of purchase requiredWhat you will learnDevelop memory models to retain short-term and cross-session contextCraft semantic blueprints and drive multi-agent orchestration with MCPImplement high-fidelity RAG pipelines with verifiable citationsApply safeguards against prompt injection and data poisoningEnforce moderation and policy-driven control in AI workflowsRepurpose the Context Engine across legal, marketing, and beyondDeploy a scalable, observable Context Engine in productionWho this book is forThis book is for AI engineers, software developers, system architects, and data scientists who want to move beyond ad hoc prompting and learn how to design structured, transparent, and context-aware AI systems. It will also appeal to ML engineers and solutions architects with basic familiarity with LLMs who are eager to understand how to orchestrate agents, integrate memory and retrieval, and enforce safeguards.…

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

Condición: New.

Paperback. Condición: New. Build AI that thinks in context using semantic blueprints, multi-agent orchestration, memory, RAG pipelines, and safeguards to create your own Context EngineFree with your book: DRM-free PDF version + access to Packt's next-gen Reader*Key FeaturesDesign semantic blueprints to give AI structured, goal-driven contextual awarenessOrchestrate multi-agent workflows with MCP for adaptable, context-rich reasoningEngineer a glass-box Context Engine with high-fidelity RAG, trust, and safeguardsBook DescriptionGenerative AI is powerful, yet often unpredictable. This guide shows you how to turn that unpredictability into reliability by thinking beyond prompts and approaching AI like an architect. At its core is the Context Engine, a glass-box, multi-agent system you'll learn to design and apply across real-world scenarios.Written by an AI guru and author of various cutting-edge AI books, this book takes you on a hands-on journey from the foundations of context design to building a fully operational Context Engine. Instead of relying on brittle prompts that give only simple instructions, you'll begin with semantic blueprints that map goals and roles with precision, then orchestrate specialized agents using the Model Context Protocol. As the engine evolves, you'll integrate memory and high-fidelity retrieval with citations, implement safeguards against data poisoning and prompt injection, and enforce moderation to keep outputs aligned with policy. You'll also harden the system into a resilient architecture, then see it pivot across domains, from legal compliance to strategic marketing, proving its domain independence.By the end of this book, you'll be equipped with the skills to engineer an adaptable, verifiable architecture you can repurpose across domains and deploy with confidence.*Email sign-up and proof of purchase requiredWhat you will learnDevelop memory models to retain short-term and cross-session contextCraft semantic blueprints and drive multi-agent orchestration with MCPImplement high-fidelity RAG pipelines with verifiable citationsApply safeguards against prompt injection and data poisoningEnforce moderation and policy-driven control in AI workflowsRepurpose the Context Engine across legal, marketing, and beyondDeploy a scalable, observable Context Engine in productionWho this book is forThis book is for AI engineers, software developers, system architects, and data scientists who want to move beyond ad hoc prompting and learn how to design structured, transparent, and context-aware AI systems. It will also appeal to ML engineers and solutions architects with basic familiarity with LLMs who are eager to understand how to orchestrate agents, integrate memory and retrieval, and enforce safeguards.…

Taschenbuch. Condición: Neu. Neuware - This book helps you transform unpredictable AI into reliable systems by building a Context Engine, a transparent, multi-agent architecture that replaces fragile prompts with structured context engineering and adapts seamlessly across domains.

Taschenbuch. Condición: Neu. Context Engineering for Multi-Agent Systems | Move beyond prompting to build a Context Engine, a transparent architecture of context and reasoning | Denis Rothman | Taschenbuch | Englisch | 2025 | Packt Publishing | EAN 9781806690053 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu. …

Paperback. Condición: New. Build AI that thinks in context using semantic blueprints, multi-agent orchestration, memory, RAG pipelines, and safeguards to create your own Context EngineFree with your book: DRM-free PDF version + access to Packt's next-gen Reader*Key FeaturesDesign semantic blueprints to give AI structured, goal-driven contextual awarenessOrchestrate multi-agent workflows with MCP for adaptable, context-rich reasoningEngineer a glass-box Context Engine with high-fidelity RAG, trust, and safeguardsBook DescriptionGenerative AI is powerful, yet often unpredictable. This guide shows you how to turn that unpredictability into reliability by thinking beyond prompts and approaching AI like an architect. At its core is the Context Engine, a glass-box, multi-agent system you'll learn to design and apply across real-world scenarios.Written by an AI guru and author of various cutting-edge AI books, this book takes you on a hands-on journey from the foundations of context design to building a fully operational Context Engine. Instead of relying on brittle prompts that give only simple instructions, you'll begin with semantic blueprints that map goals and roles with precision, then orchestrate specialized agents using the Model Context Protocol. As the engine evolves, you'll integrate memory and high-fidelity retrieval with citations, implement safeguards against data poisoning and prompt injection, and enforce moderation to keep outputs aligned with policy. You'll also harden the system into a resilient architecture, then see it pivot across domains, from legal compliance to strategic marketing, proving its domain independence.By the end of this book, you'll be equipped with the skills to engineer an adaptable, verifiable architecture you can repurpose across domains and deploy with confidence.*Email sign-up and proof of purchase requiredWhat you will learnDevelop memory models to retain short-term and cross-session contextCraft semantic blueprints and drive multi-agent orchestration with MCPImplement high-fidelity RAG pipelines with verifiable citationsApply safeguards against prompt injection and data poisoningEnforce moderation and policy-driven control in AI workflowsRepurpose the Context Engine across legal, marketing, and beyondDeploy a scalable, observable Context Engine in productionWho this book is forThis book is for AI engineers, software developers, system architects, and data scientists who want to move beyond ad hoc prompting and learn how to design structured, transparent, and context-aware AI systems. It will also appeal to ML engineers and solutions architects with basic familiarity with LLMs who are eager to understand how to orchestrate agents, integrate memory and retrieval, and enforce safeguards.…

Taschenbuch. Condición: Neu. Neuware -This book helps you transform unpredictable AI into reliable systems by building a Context Engine, a transparent, multi-agent architecture that replaces fragile prompts with structured context engineering and adapts seamlessly across domains. 396 pp. Englisch.

Condición: New.

Condición: As New. Unread book in perfect condition.

Condición: As New. Unread book in perfect condition.

Condición: New.

Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

Condición: New. Print on Demand.

Condición: New. PRINT ON DEMAND.

Paperback. Condición: new. Paperback. Build AI that thinks in context using semantic blueprints, multi-agent orchestration, memory, RAG pipelines, and safeguards to create your own Context EngineFree with your book: DRM-free PDF version + access to Packt's next-gen Reader*Key FeaturesDesign semantic blueprints to give AI structured, goal-driven contextual awarenessOrchestrate multi-agent workflows with MCP for adaptable, context-rich reasoningEngineer a glass-box Context Engine with high-fidelity RAG, trust, and safeguardsBook DescriptionGenerative AI is powerful, yet often unpredictable. This guide shows you how to turn that unpredictability into reliability by thinking beyond prompts and approaching AI like an architect. At its core is the Context Engine, a glass-box, multi-agent system youll learn to design and apply across real-world scenarios.Written by an AI guru and author of various cutting-edge AI books, this book takes you on a hands-on journey from the foundations of context design to building a fully operational Context Engine. Instead of relying on brittle prompts that give only simple instructions, youll begin with semantic blueprints that map goals and roles with precision, then orchestrate specialized agents using the Model Context Protocol. As the engine evolves, youll integrate memory and high-fidelity retrieval with citations, implement safeguards against data poisoning and prompt injection, and enforce moderation to keep outputs aligned with policy. Youll also harden the system into a resilient architecture, then see it pivot across domains, from legal compliance to strategic marketing, proving its domain independence.By the end of this book, youll be equipped with the skills to engineer an adaptable, verifiable architecture you can repurpose across domains and deploy with confidence.*Email sign-up and proof of purchase requiredWhat you will learnDevelop memory models to retain short-term and cross-session contextCraft semantic blueprints and drive multi-agent orchestration with MCPImplement high-fidelity RAG pipelines with verifiable citationsApply safeguards against prompt injection and data poisoningEnforce moderation and policy-driven control in AI workflowsRepurpose the Context Engine across legal, marketing, and beyondDeploy a scalable, observable Context Engine in productionWho this book is forThis book is for AI engineers, software developers, system architects, and data scientists who want to move beyond ad hoc prompting and learn how to design structured, transparent, and context-aware AI systems. It will also appeal to ML engineers and solutions architects with basic familiarity with LLMs who are eager to understand how to orchestrate agents, integrate memory and retrieval, and enforce safeguards. This book helps you transform unpredictable AI into reliable systems by building a Context Engine, a transparent, multi-agent architecture that replaces fragile prompts with structured context engineering and adapts seamlessly across domains. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Paperback. Condición: Brand New. 396 pages. 7.50x0.90x9.25 inches. In Stock. This item is printed on demand.