AI usage generates a fragile codebase

The use of AI in coding can lead to a fragile codebase due to simplistic test cases, lack of understanding of long-term issues, over-reliance on context windows, and ignoring of best practices. This can result in tech debt and scalability problems in large-scale SaaS applications. As a result, developers may need to revisit and refactor their code to ensure it is resilient and maintainable. This may require a shift in the way teams approach AI-generated code and prioritize code quality over speed and efficiency.