The Hidden Cost of AI-Assisted Development: Easy Code, Hard Debugging

While LLMs accelerate development and reduce coding effort, they can obscure runtime issues by generating syntactically correct code that passes automated reviews. This shift transforms debugging from preventing code errors into discovering logic and integration failures that only surface during real-world testing. For teams adopting AI-assisted workflows, the trade-off is faster feature delivery offset by potentially more elusive troubleshooting challenges.