Using ChatGPT for clean architecture in modern frameworks presents significant hurdles due to its inability to fully grasp abstract architectural principles and their nuanced application. While it can generate syntax-correct code, ensuring truly decoupled layers, strict dependency rules, and appropriate inversion of control often requires human oversight and refinement. The AI struggles to adapt generic clean architecture advice to the specific idiomatic patterns and ecosystem nuances of frameworks like React, Angular, or Spring Boot, potentially leading to suboptimal or unidiomatic implementations. There's a challenge in maintaining architectural consistency across different components or iterations, as ChatGPT might offer varied solutions based on slight prompt changes. Furthermore, it might produce seemingly correct but fundamentally flawed designs that look plausible but fail in testability, maintainability, or scalability, requiring human experts to validate and correct deep architectural decisions. Integrating its suggestions with existing codebases without introducing new technical debt or violating established conventions also proves difficult due to its limited context understanding. More details: https://www.printwhatyoulike.com/get_page?topic=59750.100&url=https://abcname.com.ua