anthony tinline (24 resultados)

Paperback. Condición: New.

Condición: As New. Unread book in perfect condition.

Condición: New.

Condición: New.

Condición: As New. Unread book in perfect condition.

Paperback. Condición: New.

Condición: New. Print on Demand.

PAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback. Condición: new. Paperback. The Multi-Agent Systems Handbook: Leveraging MCP and A2A Protocols to Build Modular, Self-Evolving AI WorkforcesMost AI systems stall at the proof-of-concept stage. A single agent works in isolation, tools break under scale, context fragments, and coordination becomes fragile. You end up with impressive demos that collapse in production.This book shows you how to architect AI systems that think, collaborate, and improve over time.The Multi-Agent Systems Handbook delivers a practical, production-focused framework for building modular, interoperable AI workforces using Model Context Protocol (MCP) and Agent-to-Agent (A2A) communication standards. Instead of hard-coding brittle tool calls, you'll design structured tool ecosystems, agent registries, and coordination layers that scale cleanly across teams and environments.Inside, you'll learn how to: Design distributed multi-agent architectures with clear role separationImplement MCP-based tool discovery, authorization, and schema validationOrchestrate agent collaboration with A2A protocols for reliable task delegationBuild memory systems that evolve with usage and feedback loopsEnforce observability, governance, and production-grade safety controlsTransition from single-agent prototypes to modular AI platformsWhether you're an AI Solutions Architect, LLM Engineer, or Multi-Agent Systems Developer, this handbook equips you to move beyond experimental scripts and into scalable AI infrastructure.How do you turn autonomous agents into coordinated digital teams?How do you prevent tool chaos, context drift, and vendor lock-in?How do you design AI systems that grow stronger with use?The answers are here.If you're ready to build AI systems that coordinate, adapt, and endure in production, this handbook is your blueprint. Start building your modular AI workforce today. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

PAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback. Condición: new. Paperback. Graph Database Performance Tuning: A Practical Playbook for Profiling Queries, Eliminating Bottlenecks, and Scaling Neo4j-Style WorkloadsYour graph database worked perfectly in development. Then production traffic hit. Queries slowed. CPU spiked. Cache misses multiplied. Suddenly, your Neo4j cluster feels fragile under real-world load.Graph workloads are powerful, but they punish inefficient query patterns, poor indexing strategies, and misconfigured memory settings. If you rely on Cypher queries for fraud detection, recommendation engines, knowledge graphs, or real-time analytics, performance is not optional. It is the difference between insight and outage.Graph Database Performance Tuning is a practical, engineering-focused guide for developers, data engineers, and solution architects who need predictable speed at scale. Instead of theory-heavy discussions, this book delivers concrete profiling strategies, execution plan analysis techniques, and production-ready optimization patterns tailored for Neo4j-style graph databases.Inside, you will learn how to: Profile and interpret Cypher execution plans with precisionIdentify cardinality explosions and hidden traversal costsDesign indexes and constraints that reduce query latencyOptimize memory configuration, page cache, and JVM settingsRefactor slow graph patterns into scalable query modelsMonitor, benchmark, and capacity-plan high-throughput workloadsScale clusters safely without sacrificing consistencyCurious why certain traversals degrade exponentially? Wondering how to structure graph schemas for sustained performance? Want to reduce query latency from seconds to milliseconds under peak load? This playbook answers those questions with clarity and actionable techniques.Whether you're running Neo4j in production, architecting enterprise knowledge graphs, or optimizing graph analytics pipelines, this book equips you with the tools to eliminate bottlenecks and scale with confidence.If performance matters to your graph systems, this is the guide to put beside your terminal. Get your copy today and start running graph workloads the way they were meant to perform. 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: new. Paperback. The Multi-Agent Systems Handbook: Leveraging MCP and A2A Protocols to Build Modular, Self-Evolving AI WorkforcesMost AI systems stall at the proof-of-concept stage. A single agent works in isolation, tools break under scale, context fragments, and coordination becomes fragile. You end up with impressive demos that collapse in production.This book shows you how to architect AI systems that think, collaborate, and improve over time.The Multi-Agent Systems Handbook delivers a practical, production-focused framework for building modular, interoperable AI workforces using Model Context Protocol (MCP) and Agent-to-Agent (A2A) communication standards. Instead of hard-coding brittle tool calls, you'll design structured tool ecosystems, agent registries, and coordination layers that scale cleanly across teams and environments.Inside, you'll learn how to: Design distributed multi-agent architectures with clear role separationImplement MCP-based tool discovery, authorization, and schema validationOrchestrate agent collaboration with A2A protocols for reliable task delegationBuild memory systems that evolve with usage and feedback loopsEnforce observability, governance, and production-grade safety controlsTransition from single-agent prototypes to modular AI platformsWhether you're an AI Solutions Architect, LLM Engineer, or Multi-Agent Systems Developer, this handbook equips you to move beyond experimental scripts and into scalable AI infrastructure.How do you turn autonomous agents into coordinated digital teams?How do you prevent tool chaos, context drift, and vendor lock-in?How do you design AI systems that grow stronger with use?The answers are here.If you're ready to build AI systems that coordinate, adapt, and endure in production, this handbook is your blueprint. Start building your modular AI workforce today. 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: new. Paperback. Engineering AI Agents with Gemini Deep Research API: The Complete Guide to Building Autonomous AgentsMost AI agents fail for predictable reasons. They hallucinate. They lose context. They burn tokens without delivering value. Teams invest weeks wiring prompts together, only to discover their "agent" is just a fragile script wrapped in hype.Engineering AI Agents with Gemini Deep Research API gives you a production-grade path forward. This book shows you how to design, build, and operate autonomous AI agents that reason over real data, conduct structured research, call tools safely, and make decisions with measurable reliability. Instead of scattered experiments, you'll build systems that stand up to real workloads.Centered on the Gemini Deep Research API, this guide walks through the architecture patterns that matter: memory buffers, multi-step reasoning workflows, tool orchestration, cost control, evaluation pipelines, and safety guardrails. You'll move beyond prompt tinkering into structured agent engineering grounded in modern LLMOps principles.Inside, you'll learn how to: Architect autonomous AI agents with scalable reasoning loopsIntegrate the Gemini API into research-driven workflowsImplement tool calling, retrieval, and memory systemsDesign evaluation and monitoring frameworks for reliabilityControl latency, token usage, and operational costDeploy agents securely in production environmentsWant agents that can research, synthesize, validate, and act with minimal supervision? Curious how to build AI systems that don't collapse under complexity?This is your blueprint for building real autonomous agents, not prototypes.If you're an AI engineer, architect, or technical founder ready to build intelligent systems that perform under pressure, start here. Add this book to your toolkit and begin engineering AI agents that deliver measurable results. 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: new. Paperback. Your AI agents work in demos. They impress in controlled environments. But when it's time to run unsupervised in production, they break, loop endlessly, overspend tokens, or stall at the first unexpected edge case.That gap between prototype and production is where most AI automation projects fail.End-to-End AI Automation with OpenClaw is a practical, engineering-focused guide to designing, orchestrating, and deploying reliable AI agents that operate without constant human supervision. Instead of fragile prompt chains, you'll build structured automation systems powered by OpenClaw's orchestration engine, deterministic workflows, and resilient execution patterns.This book shows you how to design AI automation that is predictable, testable, and production-ready. You'll learn how to connect LLMs, tools, APIs, and data pipelines into cohesive agent systems that can reason, act, validate, and recover from failure.Inside, you'll gain the ability to: Architect scalable AI agent backends with OpenClawImplement multi-step orchestration with state management and guardrailsDesign failure recovery, retries, circuit breakers, and loop detectionOptimize token usage, cost control, and execution performanceIntegrate CI/CD pipelines for automated agent testing and deploymentDeploy AI automation workflows across cloud and local environmentsWant AI systems that triage tickets, refactor code, generate documentation, run compliance checks, or manage workflows automatically? Want them to do it reliably, not just impressively?This book gives you the engineering blueprint.If you're an AI automation engineer, software developer, or technical founder ready to ship production-grade AI agents, End-to-End AI Automation with OpenClaw will give you the frameworks, patterns, and implementation strategies to build systems that actually run.Build automation that doesn't need babysitting.Get your copy today and start shipping AI that works. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.