AI Engineering
by Chip Huyen
Chip Huyen's practical guide to building production AI systems beyond research prototypes.
"Building AI systems is 10% modeling and 90% everything else no one tells you about.".
Editorial Summary
AI Engineering by Chip Huyen provides a comprehensive framework for designing, building, and deploying machine learning systems in production environments. Rather than focusing on deep learning theory or large language models in isolation, Huyen addresses the full lifecycle of AI engineering—from data collection and model training to serving, monitoring, and continuous improvement. The book draws on real-world case studies from industry leaders and emphasizes practical patterns that distinguish successful AI deployments from failed research projects. Chip Huyen, an AI infrastructure expert known for her work on machine learning systems, offers actionable guidance on tooling, architecture decisions, and organizational practices that enable teams to move beyond experimentation into reliable, scalable AI products.
Perspective
"Read this if you're building AI systems in production and tired of tutorials that stop at model accuracy metrics—Huyen fills the critical gap between academic machine learning and real-world deployment that most engineers face today. Essential for anyone shipping AI products in the post-ChatGPT era who needs to understand data pipelines, monitoring, and system design beyond prompt engineering and fine-tuning."
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