Engineering AI Systems: Architecture and DevOps Essentials
by Len Bass, Qinghua Lu, Ingo Weber, Liming Zhu
1
Introduction
Science is about knowing; engineering is about doing.
—Henry Petroski
Software development is a team sport. Different skills and perspectives are essential to build high-quality software.
—Martin Fowler
ARTIFICIAL INTELLIGENCE (AI) is the topic of our time. But let’s face it: Not everyone is an expert in both software engineering (SE) and AI. Even among AI experts, not all of the concepts that were developed for “narrow machine learning” apply to emerging new technologies like foundation models. Yet, the behavior of systems depends on all components. That’s why it’s important to get all of it right: the AI parts and the non-AI parts, the architecture, the Dev and the Ops, and all relevant quality requirements. We need to engineer ...
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