Architecting a minimum viable product (MVP) occurs under significant time pressures. AI offers assistance by suggesting alternatives based on collective experiences, which aids teams in making more informed decisions. Although AI cannot independently make architectural decisions, it can generate necessary supporting code for experiments validating these decisions. The core focus of software architecture is on capturing decisions and making trade-offs among Quality Attribute Requirements, where AI can provide valuable insights and streamline the architecting process.
Creating an effective architecture for an MVP takes time that teams seldom have; AI helps buy them time to deliver better results.
AI will enhance rather than replace software architects by better informing their decisions and automating mundane tasks to free them to discover more creative solutions to meet architectural challenges.
#software-architecture #minimum-viable-product #artificial-intelligence #decision-making #quality-attributes
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