{ "item_title" : "The Enterprise GenAI Stack", "item_author" : [" Laurel Pan", "Bing Zhang "], "item_description" : "Most enterprise GenAI maps are shelves of product logos, and the logos move every quarter. This book sets a baseline instead: the enterprise GenAI stack as it stands at the start of Q4 2026, built from 2,602 logged sources, with its high-risk claims re-checked by two adversarial verifiers.Volume 1 sets out a reference architecture for the enterprise GenAI stack, worked through for a regulated asset manager or financial-services firm: nine layers, from foundation models to evaluation, under a firm-owned control plane of eight components (gateway, guardrails, privacy, identity, configuration, FinOps, security and model risk). The layer and control chapters and the product assessments apply to any enterprise; each chapter has one section that applies the regulated financial-services lens.The central argument is that the control plane a firm owns around its products is the architecture. Products change every quarter; accountability, controls and evidence are what last.What is insideA reference architecture for regulated firms, layer by layer (L1 to L9) and control by control (C1 to C8)144 products assessed on one rubric, with Strategic, Tactical and Experimental tiers and the conditions that attach to eachFour reference stacks, a build-versus-buy view, lock-in by layer and an 18-month roadmapThe EU AI Act, DORA, the UK critical third-party regime and model-risk rules applied to GenAIOne worked example throughout: an agent drafting a fund's monthly attribution commentary, approved by a portfolio managerEvery claim is labelled as a verified fact, a reported fact, an architectural judgement, a recommendation or not publicly verified, and every fact traces to a dated source.Who it is for: enterprise and solution architects, technology and risk leaders, and the engineers, compliance and audit teams who must make GenAI work inside a regulated firm.Volume 2 re-reads the same stack for six further views: technology service providers, software product companies, start-ups, and the vendors who sell AI tools, agentic software-development tools and agents into the enterprise.By Bing Zhang, a senior technology leader in global enterprise software engineering, who pioneered and directs an organisation's agentic transformation: a move to AI-native engineering and an agentic software-development lifecycle.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/9/79/816/476/9798164767648_b.jpg", "price_data" : { "retail_price" : "39.99", "online_price" : "39.99", "our_price" : "39.99", "club_price" : "39.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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