The Demo-to-Reality Gap: 5 Architecture Decisions for Production AI Success

Most AI systems fail in production not because algorithms are flawed, but because they weren't architected for real-world unpredictability and edge cases. This article reveals the 'week-6 demo gap'—why systems work perfectly in controlled settings but break under production conditions—and provides 5 essential architecture patterns (evaluation frameworks, confidence thresholding, graceful degradation) that determine whether AI becomes a compliance risk or a reliable asset in regulated industries like fintech and healthcare.