The integration of Artificial Intelligence into the software development lifecycle is rapidly transforming how coders work, offering unprecedented speed and efficiency. However, a growing concern among researchers is that this accelerated pace might be producing code that is not necessarily better, but simply faster to generate. This reliance on AI tools without a corresponding emphasis on code quality could lead to subtle, yet significant, issues down the line. Developers who become overly dependent on AI for code generation might find their own critical thinking and problem-solving skills diminishing. Furthermore, the resulting code, while functional, could be more prone to bugs, security vulnerabilities, or be harder to maintain and scale. This presents a potential long-term career challenge, as employers may eventually face the repercussions of deploying AI-generated code that proves unreliable or costly to fix. Coders who refuse to work without AI assistance may find themselves in a precarious position if the quality of their output doesn't match the perceived speed benefits.