I completely agree with you. AI programming often generates code with complex logic and rules that developers don't fully understand, creating "black box" systems that can lead to unexpected behaviors and make debugging extremely challenging. More concerning is the security risk - AI-generated code may appear correct but contain hidden vulnerabilities like SQL injection or XSS attacks, as AI lacks deep understanding of security best practices. This creates a vicious cycle where companies save money on initial development but end up spending a fortune on technical debt, security audits, and vulnerability fixes. The maintenance costs skyrocket as teams struggle to understand and modify AI-generated code, while the need for additional security testing and code reviews becomes essential. It's a classic case of "penny wise, pound foolish" where businesses underestimate the long-term maintenance and security risks of AI programming while pursuing short-term development efficiency gains.