Description

Business-Ready Generative AI: Context Engineering, Agents, Memory, and LLMs for Real-World Applications is a deeply practical and visionary guide to building enterprise-grade generative AI systems that go far beyond standalone chatbots. Designed for real-world deployment, this book shows how to architect intelligent, scalable, and secure AI solutions using context engineering, adaptive agents, memory-driven large language models, and multimodal reasoning.

Rather than focusing on surface-level AI features, this book dives into the structural foundations required to make generative AI reliable, cost-efficient, and impactful in business environments. Readers learn how to design AI controllers, orchestrate multi-agent systems, implement short-term and long-term memory, and integrate Retrieval-Augmented Generation with live enterprise data. Each concept is explained through clear architectural thinking, actionable frameworks, and original enterprise-focused case studies.

The book explores how context engineering can dramatically improve reasoning quality while reducing token usage, how Chain-of-Thought and multimodal techniques enable complex decision-making, and how modern organizations can safely integrate multiple models without disrupting existing systems. Equal attention is given to AI ethics, governance, security, and compliance, ensuring solutions are production-ready and trustworthy.

Written in a visionary yet grounded tone, each chapter functions as a mini engineering playbook, combining strategic insight with hands-on guidance. This book equips AI engineers, architects, and technical leaders with the knowledge needed to design intelligent systems that automate workflows, enhance decision-making, and deliver measurable business value across marketing, operations, logistics, and customer service.