ISBN: 9798250309486 - ai agent engineering with n8n and mcp: designing tool-integrated llm workflows, model context protocol systems, and production-ready automation architectures (7 resultados)

Condición: As New. Unread book in perfect condition.

Condición: As New. Unread book in perfect condition.

Condición: New.

Condición: New.

Condición: NEW.

Taschenbuch. Condición: Neu. Neuware - The Automation Layer Is Evolving, Most Systems Are Not Ready>Yet most implementations fail under real-world conditions. Workflows break when tools return unexpected outputs. Context is lost between executions. Multi-step processes produce inconsistent results. Scaling exposes reliability gaps. Observability is missing. And few engineers design agents with production architecture in mind. The result: fragile automation. This book addresses the gap between prototype AI agents and production-grade automation systems. From Workflow Automation to Intelligent Agent Infrastructure>When properly engineered together, they form a powerful foundation for: - Tool-integrated LLM agents- Context-aware automation workflows- Multi-agent task coordination- API-driven intelligent systems- Scalable AI infrastructureBut building reliable AI agents requires more than connecting nodes in a visual editor. It demands architectural thinking.>What This Book DeliversThis is not a beginner tutorial.It is a technical engineering guide for building resilient AI automation systems.Inside, you will learn how to: - Design modular AI agent architectures using n8n as an orchestration engine- Implement Model Context Protocol (MCP) for standardized tool integration- Engineer tool-calling pipelines with structured validation layers- Build context management systems for persistent and session-based memory- Develop multi-agent coordination patterns for complex workflows- Handle failure modes in tool execution and LLM reasoning- Introduce observability and logging into AI workflows- Implement retry, fallback, and guardrail mechanisms- Deploy AI agents in production environments with scalable infrastructure- Secure agent systems with access control and governance controls- Optimize latency, cost, and throughput in automation pipelines- Structure enterprise-ready AI automation architecturesEach chapter builds progressively from foundational architecture principles to advanced deployment strategies. Designed for Technical PractitionersThis book is written for: - Automation engineers building AI-enabled workflows- Backend developers integrating LLMs with APIs- AI consultants designing intelligent process automation- Technical founders deploying AI-driven systems- DevOps engineers responsible for production AI workflowsIt assumes familiarity with: - APIs and RESTful systems- Basic LLM concepts- Workflow automation platforms- JSON and structured dataNo prior MCP experience is required; it is covered in depth. Who This Book Is Not ForThis book is not: - A no-code beginner tutorial- A motivational guide to AI entrepreneurship- A generic prompt engineering handbook- A hype-driven exploration of AI trendsIt is a technical manual focused on engineering discipline and practical deployment. …

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