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Artificial intelligence is changing software engineering, with major companies like Meta and Amazon investing in AI to automate coding tasks. This shift has led to concerns about the future of junior coding jobs and the overall quality of AI-generated code. While AI promises faster development, experienced programmers are raising questions about the real productivity gains and risks involved.
Vlad Mihalcea, author of High-Performance Java Persistence, recently highlighted the challenges of using AI to write code. He argued that reviewing and validating AI-generated code often erases the time savings promised by these tools. Mihalcea stated, "Reviewing code generated by AI offsets all the productivity gains you get by using AI. It takes a lot of effort to review and validate changes, and you cannot do that for 8 hours per day."
Mihalcea also warned that in large-scale projects, where mistakes can be costly, the benefits of AI are limited. He said, "Unless you are vibe coding, the actual productivity gains are marginal in large projects where software mistakes cost a lot of money." His comments reflect a growing skepticism among senior engineers about the true impact of AI on software development.
Bjarne Stroustrup, creator of the C++ programming language, has also voiced concerns about AI-generated code. According to reports, Stroustrup noted that some senior developers are choosing to retire rather than manage the poor quality of code produced by AI systems. He emphasized that, especially in programming language design, human-written code using abstraction and deep understanding remains essential. "I think that in the field I’m mostly interested in [programming language design] – code will still be written by humans, and they will use abstraction," Stroustrup said.
Linus Torvalds, the creator of Linux, has criticized exaggerated claims about AI's capabilities. According to Zdnet, Torvalds said he becomes angry when people claim that AI writes nearly all their code. "My opinion has always been that AI is a great tool, but it's a tool," he stated. Torvalds acknowledged that AI can improve developer productivity, comparing its impact to that of compilers, which translate human-readable code into machine code. He suggested AI tools could increase productivity "by a factor of 10." However, he stressed the importance of understanding both the prompts given to AI and the resulting code. "You need to understand not just your prompts, but you need to understand the end result too, because that's the only way you can maintain it long term," Torvalds said.
Despite AI's ability to generate code quickly, experienced programmers agree that humans must still review and maintain the code. The consequences of errors in AI-generated code can be significant, especially in complex or large-scale projects. As the use of AI in software engineering grows, the need for skilled human oversight remains clear.
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