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Architecting Agentic Intelligence with LangGraph+MCP+Ollama: A Practical Developer's Guide to Building Autonomous AI Systems with Graph-Based Reasoning, Multi-Agent Control, and Local Model Execution

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Fuera de stock

Peso con empaque:
0.33 kg

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No

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Nuevo

Producto de:
Amazon

Sobre este producto

LangGraph Foundations: Craft branching, looping, and memory-driven workflows with full execution visibility and testability.
MCP for Multi-Agent Orchestration: Assign tasks, route messages, spawn specialized agents, and coordinate entire agent lifecycles in runtime.
Ollama-Powered Local Reasoning: Run Mistral, LLaMA2, Codellama, and others—offline, with full control, low latency, and zero cloud costs.
Real-World Projects: From research assistants and coding copilots to DevOps operators and CSV-to-Insights agents—every chapter walks you through actual working code that’s ready to fork or deploy.
Tool and API Integration: Call Python functions, hit REST endpoints, trigger GitHub audits, read file systems, or refactor code—all from your agent.
Long-Term Memory Management: Tiered compression, token tracking, external Redis/Chroma storage, scoped memory pools—engineered for scale.
Error Recovery and Debugging Patterns: Log everything. Trace everything. Test every edge. The book shows you how to build agents you can trust.
Deployment and Optimization: Dockerize your agents, hook into CI/CD pipelines, batch tasks, trim graph overhead, and optimize for latency and token cost.
Limitations and Control Mechanisms: Learn how to prevent looping, hallucinations, tool misuse, and role confusion with fail-safes and guardrails.
Human-in-the-Loop Strategies: Implement escalation, review approvals, memory justification, and role overrides for high-stakes decisions.
Future-Ready Architectures: Role-shifting agents. Dynamic graphs. Evolvable workflows. Generalist intelligence. It's all here.
Backend and platform engineers building AI-powered internal tools
R&D teams exploring LLM automation workflows
Architects designing scalable, explainable AI systems
Security-conscious developers needing local agentic intelligence
Anyone tired of chat loops and looking to engineer real software with brains

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Architecting Agentic Intelligence with LangGraph+MCP+Ollama: A Practical Developer's Guide to Building Autonomous AI Systems with Graph-Based Reasoning, Multi-Agent Control, and Local Model Execution

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Architecting Agentic Intelligence with LangGraph+MCP+Ollama: A Practical Developer's Guide to Building Autonomous AI Systems with Graph-Based Reasoning, Multi-Agent Control, and Local Model Execution

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