Start Building Practical AI Engineering Skills Today

Follow a roadmap, GenAI prototypes to production-ready multi-agent systems. Apply design patterns, RAG, prompt and context engineering, and LLMOps to build robust agentic AI solutions, guided by case studies and a step-by-step GenAI maturity model.

This is a hands-on guide to building intelligent AI systems that augment LLMs with real-world knowledge and autonomous decision-making. You'll learn to integrate retrieval, knowledge graphs, and multi-agent techniques for advanced problem-solving.

This hands-on guide equips you to design and build 30 intelligent agents for modern, autonomous AI systems. From foundational cognitive loops to complex multi-agent orchestration, you will learn to create production-ready solutions using scalable architectures for real-world, domain-specific applications.

Master the design of agentic AI systems from the ground up. This hands-on guide shows you how to build your own framework in Python, integrate memory and context with MCP, and implement multi-agent collaboration through A2A protocols.

This book helps you transform unpredictable AI into reliable systems by building a Context Engine, a transparent, multi-agent architecture that replaces fragile prompts with structured context engineering and adapts seamlessly across domains.

Grasp the fundamentals of agentic systems and a deep understanding of the essential building blocks of intelligent agents with this comprehensive guide that bridges theory and practice, empowering you to create sophisticated AI systems.

This book is your fast-track guide to building smarter, scalable, and AI-integrated Python-based applications using MCP. You'll learn to develop, integrate, and deploy MCP-powered systems with ease.

Multi-agent systems are reshaping how AI is built. This practical engineering guide gives you the principles, design patterns, and operational discipline to take agentic AI from clever demos to reliable production at scale.

This book helps you to build, orchestrate, and deploy AI agents for real-world applications. You'll learn to create single and multi-agent systems that leverage LLMs, tools, and memory to solve complex business problems across industries.