Runtime Intelligence: The New AI Architecture bundle 
AI is entering a new phase. For years, progress meant building bigger models with more parameters and more training data. But the most important shift happening right now isn’t about model size, it’s about how systems think at runtime. AI labs are discovering that models can become dramatically more capable not by getting larger, but by getting more time and structure to reason. From OpenAI’s reasoning systems to DeepSeek’s R1, a new architecture is emerging: one where intelligence improves the longer a system has to think. This book bundle explores why test-time compute, reasoning loops, and reinforcement learning are becoming the foundation of modern AI systems and how forward-thinking teams are already building around this approach. If you’re working with LLMs, agents, or AI-powered products, understanding this shift is no longer optional. It’s the difference between building yesterday’s chatbots and tomorrow’s intelligent systems.
Build a Reasoning Model (From Scratch) 
In Build a Reasoning Model (From Scratch), acclaimed ML research engineer Sebastian Raschka takes you inside the black box of reasoning-enhanced LLMs. You’ll start with a compact, pre-trained base model that runs on consumer hardware, then upgrade it step by step to tackle ever-more difficult problems and scenarios. You’ll measure its performance, add reasoning at inference time without training, and then improve it further with reinforcement learning. By the end of the book, you’ll have a small but capable reasoning stack built from the ground up!
Introduction to Generative AI, Second Edition
Introduction to Generative AI, Second Edition is a completely revised and updated guide to the capabilities, risks, and limitations of generative AI. You’ll understand the latest innovations in AI, AI agents, multimodal training, reasoning models, retrieval-augmented generation (RAG), and more. Along the way, you’ll explore how AI is impacting the world, with an expert-level look at AI in industry, education, and society.
Sutskever's List
In Sutskever’s List, author Rich Heimann takes you on a tour through Sutskever’s List in his accessible and insightful style, unpacking each paper with clear explanations, vivid historical anecdotes, and examples that connect lab results to real-world consequences. You’ll follow the story of modern AI, from scaling laws to internal organizational politics, as Rich demystifies the complex research and simple human choices that gave rise to artificial intelligence. And unlike the 30 amazing papers Rich interprets, this accessible book requires no specialist knowledge!
The RLHF Book
The RLHF Book explores the ideas, established techniques and best practices of RLHF you can use to understand what it takes to align your AI models. You’ll begin with an in-depth overview of RLHF and the subject’s leading papers, before diving into the details of RLHF training. Next, you’ll discover optimization tools such as reward models, regularization, instruction tuning, direct alignment algorithms, and more. Finally, you’ll dive into advanced techniques such as constitutional AI, synthetic data, and evaluating models, along with the open questions the field is still working to answer. All together, you’ll be at the front of the line as cutting edge AI training transitions from the top AI companies and into the hands of everyone interested in AI for their business or personal use-cases.
Some bundled books and liveVideos are part of the Manning Early Access Program. You'll get all the available content now, new content as it's created, and the final product when it's ready.
