{"product_id":"architecting-generative-ai-applications-by-leonid-kuligin-9781806678655","title":"Architecting Generative AI Applications","description":"\u003cdiv class=\"book-description\"\u003e\n\u003cp\u003eTake generative AI from prototype to production with confidence, master core LLM architectures, rigorous evaluation (offline and A\/B testing), LLMOps and deployment pipelines, and the reliability practices that keep systems stable, secure, and scalable in the real world.\u003c\/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eKey Features\u003c\/strong\u003e\u003c\/p\u003e\n\n\u003cul\u003e\n  \u003cli\u003eTurn generative AI prototypes into production-ready applications\u003c\/li\u003e\n  \u003cli\u003eMaster LLM evaluation, observability, and reliability engineering\u003c\/li\u003e\n  \u003cli\u003eDeploy and scale AI systems using LLMOps and modern DevOps tools\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003cp\u003e\u003cem\u003eArchitecting Generative AI Applications\u003c\/em\u003e provides a practical guide to building production-ready generative AI applications that are reliable, scalable, and secure, and to understanding where traditional software best practices can clash with the realities of operating LLM-based systems.\u003c\/p\u003e\n\n\u003cp\u003eWritten by a Staff AI Engineer at Google, it takes you through the full AI product lifecycle: scoping and building effective prototypes, aligning them with business goals, and scaling enterprise-wide generative AI adoption. You will learn how to evaluate LLMs with offline metrics, human-in-the-loop methods, and statistical testing.\u003c\/p\u003e\n\n\u003cp\u003eNext, you will design core architectures such as RAG, vector databases, agents, and memory systems. Operationalize these systems with production-grade code, robust testing, DevOps, MLOps, and LLMOps workflows, including deployment and scaling on modern LLMOps platforms. The book also covers security, Responsible AI, and modern observability and reliability for generative AI systems.\u003c\/p\u003e\n\n\u003cp\u003eBy the end you’ll learn how to run post-launch A\/B tests, maintain systems over time, and measure business impact. The focus is on durable engineering principles, so your products succeed beyond the prototype stage.\u003c\/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eWhat you will learn\u003c\/strong\u003e\u003c\/p\u003e\n\n\u003cul\u003e\n  \u003cli\u003eDesign offline and online evaluation strategies (including statistical A\/B testing) and collect the right data\u003c\/li\u003e\n  \u003cli\u003eConvert AI prototypes into production-ready applications that are stable, scalable, \u0026amp; secure\u003c\/li\u003e\n  \u003cli\u003eReduce maintenance effort with best practices in testing, configuration, and code readability\u003c\/li\u003e\n  \u003cli\u003eImplement DevOps, MLOps, and LLMOps—what's common and what differs across these approaches for AI systems\u003c\/li\u003e\n  \u003cli\u003eBuild platform teams to scale enterprise-wide generative AI adoption\u003c\/li\u003e\n  \u003cli\u003eDefine reliability targets using SRE principles and statistical A\/B testing\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003cp\u003e\u003cstrong\u003eWho this book is for\u003c\/strong\u003e\u003c\/p\u003e\n\n\u003cp\u003eThis book is for technical leaders, AI engineers, data scientists, software engineers, and architects building generative AI applications. It is also ideal for engineering managers, product leaders, and technical decision-makers who need to understand how to deploy, scale, and maintain production-grade AI systems.\u003c\/p\u003e\n\u003c\/div\u003e","brand":"Unknown","offers":[{"title":"Default Title","offer_id":47933827317996,"sku":"9781806678655","price":133.0,"currency_code":"NZD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0705\/7784\/8556\/files\/9781806678655-architecting-generative-ai-applications.jpg?v=1783880831","url":"https:\/\/bookhero.live\/products\/architecting-generative-ai-applications-by-leonid-kuligin-9781806678655","provider":"Book Hero","version":"1.0","type":"link"}