{"product_id":"learning-langchain-building-ai-and-llm-applications-with-langchain-and-langgraph","title":"Learning LangChain: Building AI and LLM Applications with LangChain and LangGraph by Mayo Oshin and Nuno Campos","description":"\u003ch2\u003eLearning LangChain: Building AI and LLM Applications with LangChain and LangGraph by Mayo Oshin and Nuno Campos\u003c\/h2\u003e\n\u003cp data-path-to-node=\"6\"\u003eThe core principle of \u003ci data-path-to-node=\"6\" data-index-in-node=\"22\"\u003eLearning LangChain\u003c\/i\u003e is that \u003cb data-path-to-node=\"6\" data-index-in-node=\"49\"\u003ethe value of an LLM scales exponentially when it is connected to external data fabrics, APIs, and computational state engines.\u003c\/b\u003e The authors directly confront the biggest roadblock developers face when building AI software: when an LLM operates solely on its static training weights, it suffers from information recency gaps, data hallucinations, and a total lack of long-term memory. LangChain solves this infrastructure crisis by providing a unified, modular framework of abstractions.\u003c\/p\u003e\n\u003cp data-path-to-node=\"6\"\u003eWritten by a founding engineer of the framework itself, this book skips superficial prompt-engineering tricks and dives straight into structural software engineering. \u003cspan class=\"citation-123\"\u003eIt introduces readers to the \u003c\/span\u003e\u003cb data-path-to-node=\"7\" data-index-in-node=\"196\"\u003e\u003cspan class=\"citation-123\"\u003eLangChain Expression Language (LCEL)\u003c\/span\u003e\u003c\/b\u003e\u003cspan class=\"citation-123 citation-end-123\"\u003e—a powerful, declarative syntax built to handle streaming data, parallel execution steps, and automatic fallback behaviors seamlessly.\u003csup class=\"superscript\" data-turn-source-index=\"3\"\u003e\u003c!----\u003e\u003c\/sup\u003e\u003c\/span\u003e \u003cspan class=\"citation-122 citation-end-122\"\u003eThrough clear, side-by-side Python and JavaScript architectures, the text guides developers through building data indexing systems, complex Retrieval-Augmented Generation (RAG) loops, and stateful multi-actor agent networks using LangGraph.\u003csup class=\"superscript\" data-turn-source-index=\"4\"\u003e\u003c!----\u003e\u003c\/sup\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp data-path-to-node=\"29\"\u003eAs our regional software export firms, tech startups, and freelance engineering ecosystems rush to fulfill the massive international demand for production-grade artificial intelligence systems, backend developers are hitting a major architectural wall. While writing a short Python script to interact with an AI model is trivial, software projects routinely collapse during team deployment because teams lack a structured, production-tested framework to handle complex data indexing, multi-turn chat states, and unexpected model errors.\u003c\/p\u003e\n\u003cp data-path-to-node=\"29\"\u003e\u003ci data-path-to-node=\"30\" data-index-in-node=\"0\"\u003e\u003cspan class=\"citation-118\"\u003eLearning LangChain\u003c\/span\u003e\u003c\/i\u003e\u003cspan class=\"citation-118 citation-end-118\"\u003e provides the ultimate code-forward solution to this skills bottleneck.\u003csup class=\"superscript\" data-turn-source-index=\"8\"\u003e\u003c!----\u003e\u003c\/sup\u003e\u003c\/span\u003e Written by a core LangChain engineer, this manual entirely skips superficial marketing buzzwords to deliver an intensely technical, step-by-step masterclass. By laying out clear, concrete blueprints for LCEL pipeline composition, automated vector indexing, and stateful LangGraph agent orchestrations in both Python and JavaScript, it equips local systems engineers, full-stack developers, and technical architects with the practical expertise required to build resilient, global-scale AI applications. It is a mandatory desktop companion for the modern software engineer.\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cstrong\u003eLanguage: English.\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cstrong\u003eGenre: AI Engineering\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cstrong\u003eBinding: সেলাই করা বাইন্ডিং\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cstrong\u003eQuality: Premium Quality Books.\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cstrong\u003ePrinting: High Quality Printing.\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cstrong\u003ePaper: Eye Friendly paper (Cream White)\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cstrong\u003eCover: Matt cover (Paperback).\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp data-path-to-node=\"30\" id=\"p-rc_22239127ed1c9f4c-66\"\u003e\u003c\/p\u003e\n\u003cp data-path-to-node=\"7\" id=\"p-rc_22239127ed1c9f4c-62\"\u003e\u003c\/p\u003e","brand":"Royal Books BD","offers":[{"title":"Default Title","offer_id":47231420268729,"sku":null,"price":290.0,"currency_code":"BDT","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0780\/0874\/6169\/files\/Learning_LangChain_Building_AI_and_LLM_Applications_with_LangChain_and_LangGraph.jpg?v=1779345066","url":"https:\/\/royalbooksbd.com\/products\/learning-langchain-building-ai-and-llm-applications-with-langchain-and-langgraph","provider":"Royal Books BD","version":"1.0","type":"link"}