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Table Of Contents
Architecting AI Software Systems
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Architecture emerges from requirements, creating a recursive pattern where components synthesized from initial requirements themselves become requirements for subsequent architectural synthesis. This recursion continues until system builders can no longer meaningfully impact associated sub-components, at which point implementation details take precedence.
A robust development environment serves as the foundation for testing and validating pipelines before production release. Comprehensive architecture models identify major components, external interfaces, user involvement points, and data requirements throughout the system. Multiple architecture views capture process flows and operational threads, demonstrating how AI systems will systematically meet both explicit and implicit requirements [3].
Modular design significantly enhances system flexibility and maintainability, particularly in complex AI pipelines. Each stage in an AI pipeline should be independently...
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