AI Engineering and Agentic AI: Designing Autonomous Language Model Systems with Memory, Tools, and Safe Deployment

Artificial intelligence is no longer limited to research labs, it is now a core component of modern software systems. This book provides a comprehensive, practical guide to building real-world AI applications using foundation models, large language models, and agentic systems.AI Engineering and Agentic AI bridges the gap between theory and production. It focuses on how to design, build, evaluate, and deploy intelligent systems that can reason, act, and interact reliably in real-world environments.Inside this book, you will learn how to:Understand how large language models work and where they succeed and failDesign effective prompts and structured prompt systems for consistent outputsBuild retrieval-augmented generation (RAG) systems grounded in real dataDevelop AI agents with memory, tools, and multi-step reasoning capabilitiesArchitect scalable workflows and multi-agent systemsEvaluate AI systems using practical metrics and benchmarksDeploy, monitor, and optimize AI applications in productionManage cost, latency, safety, and compliance risksApply AI across industries including business, software, healthcare, and educationUnlike many resources that focus only on models or theory, this book emphasizes end-to-end system design. It reflects current industry practices, including agent frameworks, evaluation pipelines, and real-world deployment strategies.Whether you are a software engineer, data scientist, technical leader, or an ambitious beginner, this book equips you with the knowledge needed to move from experimentation to production-ready AI systems.Key FeaturesPractical, system-oriented approach to AI engineeringCoverage of both prompt engineering and agentic AIReal-world examples and deployment insightsClear explanation of modern tools, frameworks, and architecturesFocus on reliability, safety, and scalability Read more