IBM’s Guidance and Official Materials
IBM’s RAG Cookbook: IBM offers a comprehensive "RAG Cookbook," designed as a practical guide for technical professionals seeking to build or optimize RAG-based AI pipelines. This resource covers architectures, best practices, and integration tips for deploying RAG solutions in enterprise environments. While RAG and Agentic AI are closely linked in advanced AI system designs, IBM typically addresses them as separate topics: practical RAG solutions and the architectural/topical aspects of Agentic AI. The Cookbook steers users to IBM's Agent Development Portal for more in-depth work on agentic systems.
Agentic AI with IBM: IBM defines Agentic AI as the construction of autonomous AI agents capable of carrying out specific goals with minimal supervision, often by combining retrieval-augmented techniques with agent workflows. IBM’s online resources provide deep dives into both topics, making them accessible to AI practitioners and business leaders alike.
Professional Certification: IBM offers a "RAG and Agentic AI Professional Certificate" through Coursera, guiding learners through RAG pipeline building, multimodal integration, and agent orchestration—ideal for those looking to develop production-grade, agentic AI solutions.
Books Covering RAG and Agentic AI (2024–2025)
Agentic AI with RAG in Action by Ronald Taylor (2025)
This book delivers a hands-on guide to building, scaling, and deploying autonomous AI agents using RAG. Readers learn practical prompt engineering, workflow design, case studies, and ethics for deploying agentic systems with retrieval-augmented backends. It blends technical details (code samples, architecture diagrams) with real-world application strategies, making it popular among AI developers and digital innovators.
Agentic AI System Leveraging RAG by Jerry Canter (2025)
Focused on practical frameworks, this guide integrates agentic system design with RAG 2.0, including cognitive architectures, advanced retrieval strategies, and real-time data handling. It addresses AI ethics, scalability, and implementation challenges, all through a lens of industrial use cases.
Agentic Artificial Intelligence: Harnessing AI Agents to Reinvent Business, Work, and Life by Pascal Bornet, Jochen Wirtz, and Thomas H Davenport (2025)
While not exclusively IBM-centric, this influential business guide demystifies agentic AI. It surveys hands-on deployments across major enterprises (including those using IBM systems), explains how agentic AI transforms industries, and offers strategic roadmaps for leaders. The book mixes case studies, technical explanations, and future trends for non-technical audiences as well.
Mastering Agentic AI in Cloud and Edge Computing by Brian Pitman (2025)
This book targets engineers and business leaders seeking a blend of RAG, agent architecture, and cloud/edge applications, supplying detailed coding guides, business case studies, and production design insights.
RAG-Driven Generative AI by Denis Rothman (2024)
This technical reference explains how to implement custom RAG pipelines with various open-source and IBM-relevant technologies, including best practices for minimizing hallucinations and supporting multimodal agents. It connects RAG’s impact to broader generative/agentic strategies in real-world applications.
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