ENTERPRISE AI ARCHITECTURE AND THE MODERN AI STACK

Description

Welcome to the Leanpub Launch video for ENTERPRISE AI ARCHITECTURE AND THE MODERN AI STACK: VOLUME I — DESIGNING THE STACK https://leanpub.com/enterprise-ai-architecture by Padmanabham Venkiteela! 0:00 Author introduction and overview of the two-volume book series 0:50 Book structure: 10 layers, 10 tools per layer, ~100 tools total 1:40 Layer 1 – Foundation models: OpenAI, Anthropic, Google, DeepSeek, Mistral and more 2:28 Layer 2 – Interoperability protocols: MCP, A2A, AI gateways, and OpenRouter 3:14 Layer 3 – Agent frameworks: LangGraph, CrewAI, Autogen, OpenAI Agent SDK 3:59 Layer 4 – Vector databases, embedding models, and retrieval orchestration 5:32 Layer 5 – AI coding tools: Claude Code, Cursor, GitHub Copilot, and benchmarking 6:17 Volume II preview: ML Ops, model training, fine-tuning, and serving infrastructure 7:51 Observability and governance: monitoring agents, guardrails, and enterprise security 9:28 Using the book as a reference tool: checklists, comparison matrices, and ROI guidance About the Book Artificial Intelligence is rapidly transforming how enterprises build software, automate business processes, and make decisions. Yet many organizations struggle to move beyond isolated AI experiments because they lack a clear architectural foundation for integrating AI into complex enterprise environments. Enterprise AI Architecture and the Modern AI Stack – Volume I: Designing the Stack provides that foundation. This book presents a practical, vendor-neutral framework for designing enterprise-grade AI systems that are secure, scalable, governed, and production-ready. Rather than focusing on individual AI models or coding techniques, it explains how every layer of the modern AI ecosystem fits together—from infrastructure and data platforms to Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, orchestration frameworks, APIs, governance, security, and enterprise integration. Drawing on nearly two decades of experience in enterprise architecture, cloud integration, API management, and digital transformation, the author bridges the gap between traditional enterprise architecture and the rapidly evolving world of Generative AI and Agentic AI. Inside this book, you will learn: The complete Enterprise AI technology stack and how each layer works together How Large Language Models fit into enterprise architecture The role of vector databases, embeddings, and Retrieval-Augmented Generation (RAG) AI agents, orchestration frameworks, and Model Context Protocol (MCP) Secure API-first AI architectures for enterprise environments Enterprise governance, compliance, and responsible AI practices Reference architectures and design patterns for production AI systems How to evaluate AI platforms, frameworks, and infrastructure using architectural principles Whether you are an Enterprise Architect, Solution Architect, Integration Architect, AI Engineer, Engineering Leader, CTO, Technology Executive, or software professional preparing for the next generation of enterprise systems, this book provides the architectural blueprint needed to design modern AI-enabled enterprises. This is not a book about prompting or building simple chatbots. It is a comprehensive guide to designing the enterprise AI platforms that organizations will rely on for the next decade. Volume I: Designing the Stack is the first book in the Enterprise AI Architecture series and establishes the architectural principles that underpin modern enterprise AI. Future volumes will build on this foundation by exploring enterprise AI patterns, implementations, governance, industry use cases, and advanced architectural frameworks. About the Author Padmanabham Venkiteela is an Enterprise AI Architect, researcher, technical author, and international conference speaker with nearly two decades of experience designing and modernizing enterprise technology platforms. His expertise spans Enterprise AI, Agentic AI, API-led architecture, enterprise integration, cloud computing, and digital transformation. Throughout his career, he has led large-scale enterprise modernization initiatives involving SAP Integration Suite, Google Cloud, Oracle Integration Cloud, Boomi, API Management, event-driven architectures, and AI-powered enterprise solutions. His work focuses on helping organizations build scalable, secure, and intelligent systems by combining large language models (LLMs), Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), AI agents, APIs, and cloud-native architectures. Padmanabham is an active researcher and contributor to the Enterprise AI community through technical publications, conference presentations, peer review, judging, and professional speaking engagements. He is passionate about bridging the gap between traditional enterprise architecture and the rapidly evolving world of Generative AI and Agentic AI. He is the author of AI Generalist Engineer, a practical guide designed to help architects, software engineers, AI practitioners, and technology leaders build production-ready Enterprise AI systems using modern AI frameworks and engineering best practices. When not researching emerging AI technologies, he enjoys mentoring technology professionals, contributing to the global AI community, and exploring the future of intelligent enterprise systems. Learn more at www.padmanabhamvenkiteela.com. Follow the author here! https://x.com/Padmanabham Venkiteela Thank you for watching, please like and leave a comment, we'd love to hear from you! Please Subscribe and Follow! YouTube: https://www.youtube.com/leanpub X: https://x.com/leanpub Instagram: https://www.instagram.com/leanpub Facebook: https://www.facebook.com/leanpub Create Your Own Leanpub Book! 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