AI agents are showing up everywhere—and most of them are being built by trial and error. This guide distills the experience of a growing community of agent builders into 20+ composable, reusable patterns for building AI agents that are reliable, efficient, controllable, and easy to reason about. In this uniquely-valuable book, author and NVIDIA Research scientist Peter Belcak gives you a durable engineering vocabulary and design intuition that outlasts any new model release. [Read more] 5 chapters of this MEAP are available now, with more to follow soon!
Algorithms Every Programmer Should Know
Traditional algorithm textbooks rely on encyclopedic depth, mathematical rigor, and pseudocode. This book takes a human approach, placing you in a reading group where three individuals discuss, question, and reason through key computer science algorithms. Each chapter builds intuition through relatable analogies and discussion before applying the algorithm to practical systems like routing, scheduling, string search, caching, and optimization. [Read more] 6 chapters of this MEAP are available now, with more to follow soon!
Generative AI is changing how people work, but getting real value from it requires understanding both its capabilities and its limitations. This accessible, jargon-light introduction covers large language models, prompt engineering, model selection, retrieval-augmented generation, and AI agents. It also addresses hallucinations, bias, privacy, and over-reliance on AI, giving professionals, educators, managers, students, and creators the knowledge they need to use modern AI confidently and critically. [Read more] 3 chapters of this new MEAP are available now, with more to follow soon!
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