
An Illustrated Guide to AI Agents: Concepts and Code for Building Agents with LLMs, Tools, and Memory
Author(s): Maarten Grootendorst (Author), Jay Alammar (Author)
- Publisher Finelybook 出版社: O’Reilly Media
- Publication Date 出版日期: October 13, 2026
- Edition 版本: 1st
- Language 语言: English
- Print length 页数: 448 pages
- ASIN: B0GTYL2QSJ
- ISBN-13: 9798341662698
Book Description
Artificial intelligence is entering a new phase. No longer limited to answering prompts or completing simple writing tasks, AI agents can now reason, plan, and act with increasing independence. From accelerating scientific breakthroughs to supporting creative work, these systems are quickly reshaping industries and everyday life. This book provides the conceptual foundation and practical insights you need to understand—and effectively work with—this emerging technology.
Through hundreds of clear graphic illustrations, Maarten Grootendorst and Jay Alammar explain how AI agents are built, how they think, and where they’re heading. Designed for professionals, students, and curious learners alike, this guide goes beyond the buzz to reveal what’s actually happening inside these systems, why it matters, and how to apply the knowledge in real-world contexts. With its visual storytelling and accessible explanations, An Illustrated Guide to AI Agents is your essential reference for navigating the next frontier of artificial intelligence.
- Explore the core architecture of AI agents: tools, memory, and planning
- Understand reasoning LLMs, multimodal models, and multi-agent collaboration
- Learn advanced methods, including distillation, quantization, and reinforcement learning
- Evaluate real-world applications, strengths, and limitations of AI agents
Editorial Reviews
Editorial Reviews
About the Author
Jay Alammar is director and engineering fellow at Cohere (pioneering provider of secure AI for the enterprise). In this role, he conducts machine learning research improving the agentic and tool use abilities of large language models. Through his popular AI/ML blog (https://jalammar.github.io) and Substack (https://newsletter.lan guagemodels.co), Jay has helped millions of researchers and engineers visually understand, use, and build machine learning tools, concepts, and models. Jay is also a co-creator of popular machine learning and natural language processing courses on Deeplearning.ai and Udacity.
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