The discussion surrounding the impact of Generative AI (GenAI) on computer programming has been marked by significant hype, with claims that it could enhance programmer productivity by a factor of ten. However, recent data and studies suggest that these expectations may be overly optimistic. Gary Marcus highlights that after 18 months of anticipation regarding GenAI's potential to revolutionize coding, the evidence does not support the notion of a tenfold increase in productivity. Two recent studies illustrate this point: one involving 800 programmers found minimal improvement and an increase in bugs, while another study indicated a moderate 26% improvement for junior developers but only marginal gains for senior developers. Additionally, earlier research pointed to a decline in code quality and security, raising concerns about the long-term implications of relying on GenAI tools. Marcus argues that the modest improvements observed, coupled with potential drawbacks such as increased technical debt and security vulnerabilities, indicate that the reality of GenAI's impact is far from the promised tenfold enhancement. He suggests that a good Integrated Development Environment (IDE) might offer more substantial and reliable benefits for programmers than GenAI tools. The underlying reason for the lack of significant gains, according to AI researcher Francois Chollet, is that achieving a tenfold increase in productivity requires a deep conceptual understanding of programming, which GenAI lacks. While these tools can assist in speeding up the coding process, they cannot replace the critical thinking necessary for effective algorithm and data structure design. Marcus reflects on his own experience as a programmer, noting that clarity in understanding tasks and concepts has historically been a greater advantage than any tool could provide. In the comments section, other programmers echo Marcus's sentiments, sharing their experiences with GenAI coding assistants like Copilot and ChatGPT. Many report that while these tools generate more code, they often introduce bugs and require additional time for debugging, ultimately detracting from productivity rather than enhancing it. Overall, the initial excitement surrounding GenAI's potential to transform programming practices is tempered by the reality of its limitations, emphasizing the importance of foundational knowledge and critical thinking in software development.