This Manning Publications book teaches readers how to construct reasoning-focused AI models inspired by systems like OpenAI's o1, covering chain-of-thought training, reinforcement learning from human feedback, and search-augmented inference. It provides practical code implementations alongside the theory to help readers understand how deliberative reasoning emerges in modern LLMs. The book is suited for ML engineers and researchers looking to go beyond standard instruction fine-tuning.
