A practical, hands-on guide to building and operating your own AI stack, from lightweight homelab setups to production-ready platforms. This book includes specific code examples and walks through real architectures, covering local AI setups, deploying cloud-based platforms, exposing AI inference endpoints, and working with AI agents.
If you want to move beyond using AI APIs and start owning the full stack, infrastructure, models, and workflows, this guide shows you how to get there step by step.
Built from real-world experiments and field experience, it is designed for engineers and architects who prefer learning by doing. It serves as a practitioner’s companion for hands-on exploration. The examples are intended for learning and proof-of-concept work.
