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Architecting AI Software Systems
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Imagine walking into a restaurant where the waiter immediately tells you what you’ll eat without offering a menu, asking about your preferences, or discussing your budge – yet you’re still expected to pay. Such a restaurant would quickly fail. What’s missing? Customer engagement to understand actual needs and a mechanism for feedback. This scenario parallels what happens too often in complex software development, particularly with AI-driven systems [1].
By conducting thorough conceptual design activities, we mitigate the risks of misunderstanding user and stakeholder needs. The artifacts developed during this phase provide architects with a perspective on the system’s end goals and constraints and how customers perceive value. Conversely, these artifacts allow customers to concretize their objectives, surface major implicit assumptions, communicate with other stakeholders, and gain confidence that system builders...
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