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"All of AI... has a proof-of-concept-to-production gap."
- Andrew Ng
This gap is why most AI projects never make it past the prototype stage.
Hands-On AI Engineering is a practical, code-first guide that teaches you how to move from simple experiments to reliable, production-grade AI systems without relying on expensive cloud credits or black-box APIs.
This book focuses on the real decisions you face when building AI applications: evaluation strategy, cost control, reliability, guardrails, and deployment trade-offs.
What You'll Learn
Table of contents
Hands-On AI Engineering gives you the guidance needed to move you from an experiment to a dependable system.
Also includes 6 fully working GitHub projects you can run locally, from basic RAG to evaluated systems, agents with memory, and study tools. These projects mirror modern team workflows and give you something concrete to show in interviews or client work.
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Take 20% off your first order
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