Direct answer
Good SaaS MVP architecture supports the first paid workflow, keeps data paths understandable, avoids premature platform complexity, and leaves room to replace fragile assumptions after customer evidence arrives.
What older product lines teach
Magento extensions, WordPress plugins, HTML templates, and internal reporting tools are small product surfaces. Each had a defined user job, compatibility boundary, release path, and support obligation.
How that maps to AI SaaS
AI SaaS MVPs need the same discipline: define the job, keep the data path visible, constrain model responsibility, document quality checks, and ship a narrow release that creates customer evidence.
Where Sam adds value
Sam helps founders decide which parts of the architecture matter now, what can stay manual, what can be tested with a prototype, and what needs production-grade reliability from day one.