Artificial intelligence is entering a new era.

Modern AI systems are becoming increasingly capable of breaking complex problems into steps, evaluating alternatives, planning solutions, writing and analyzing code, and tackling tasks that require more than simply predicting the next word.

Reasoning Models provides an accessible, practical guide to understanding this important evolution in AI.

This book explores what reasoning models are, how they differ from traditional language models, why they can perform differently on complex tasks, and how developers, creators, professionals, and curious readers can begin building with reasoning-capable AI.

Inside, you'll discover:

• The fundamentals of AI reasoning and reasoning models
• How modern AI approaches complex problems step by step
• The connection between reasoning, inference, planning, and decision-making
• Why reasoning capabilities matter for mathematics, coding, research, analysis, and problem solving
• How prompting and structured workflows can improve AI-assisted problem solving
• Practical considerations when building applications with reasoning-capable models
• The limitations, trade-offs, and challenges surrounding AI reasoning
• How to evaluate the reliability and usefulness of reasoning-based systems
• What reasoning models could mean for AI agents and intelligent applications
• Where the technology may be heading next

Rather than treating AI as a mysterious black box, this book gives you a practical framework for understanding what is happening beneath the surface—and how to think about building useful systems with these emerging capabilities.

Whether you're new to artificial intelligence or already experimenting with AI tools and applications, Reasoning Models helps bridge the gap between theory and practical use.

Understand how AI reasons. Think differently about what's possible. Build with the next generation of AI.