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Mastering LangChain and LangGraph for AI Agents: A Practical Guide to Building Scalable LLM Applications, Multi-Agent Architectures, and Production-Re
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Publisher: Independently Published
Pages: 162
Weight: 0.64
Height: 0.35 Width: 7.00 Depth: 10.00
Language: English
This comprehensive volume provides an in-depth exploration of modern agentic architectures, offering a complete progression from foundational concepts to full-stack production systems. Readers will master the core abstractions of LangChain, the power of LangGraph for stateful multi-agent workflows, advanced reasoning techniques, retrieval-augmented generation (RAG), robust data engineering practices, comprehensive evaluation strategies, observability, secure deployment, and responsible AI governance.
Whether you are an experienced developer building enterprise AI solutions or an advanced learner aiming to bridge the gap between prototypes and production, this book equips you with the architectural vision, engineering patterns, and implementation details necessary to succeed. It addresses the full lifecycle of agentic systems from data ingestion and reasoning loops to deployment, scaling, security, and ethical considerations ensuring systems are not only powerful but also trustworthy and maintainable.
With its focus on current tools, real-world best practices, and forward-looking insights, Mastering Agentic AI Systems serves as both a thorough learning resource and an essential reference for anyone building the next generation of intelligent applications.
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