Software engineers are facing an 'identity crisis bordering on depression,' Menlo Ventures partner says

As the tech landscape rapidly evolves, software engineers find themselves navigating an unprecedented challenge, driven by the surge in AI coding tools. Deedy Das, a partner at Menlo Ventures, highlights a troubling divide within engineering teams, where two distinct groups are emerging. On one side are what Das refers to as the "lazy" engineers. These individuals heavily depend on AI to handle coding tasks, respond to queries, and manage updates, often engaging with their work at a minimal level. Conversely, the "craftsmen"—seasoned engineers—are left to contend with the overwhelming influx of AI-generated code that requires their expertise in understanding, reviewing, and correcting. Das poignantly noted in a recent social media post that many software engineers are grappling with an identity crisis that is nearing a state of depression. This concern is central to the ongoing discourse about the transformative impact of AI on the software engineering field, a topic explored in depth by Business Insider in its series "The Great Coding Reset." As organizations advocate for increased AI integration in coding practices, many engineers feel their roles are shifting away from traditional software development towards primarily overseeing, managing, and validating machine-produced work. This transition is prompting a reevaluation of their professional worth. Moreover, the phenomenon dubbed "AI sprawl"—where employees juggle multiple AI tools, often duplicating efforts and generating escalating amounts of output—complicates matters further. Amanda Hoover from Business Insider highlights the inefficiencies in this approach, raising questions about whether productivity is genuinely improving. Das emphasizes the fatigue experienced by the craftsmen who bear the brunt of the review process. He stated, "The craftsmen are tired. Very tired. The entire burden of review falls on the craftsman. The burden of understanding." As the ease of code generation through AI increases, the challenges of reviewing and maintaining that code are becoming the primary bottleneck in the development process. This shift mirrors the rise of "botsitting," a term that encapsulates the need for engineers to supervise AI outputs, rectify errors, and validate results. Das previously noted that many software engineers feel their core skills are becoming obsolete in the face of AI advancements. As a result, they often find themselves overwhelmed by the volume of pull requests, leading to a higher incidence of bugs making their way into production environments. Although Das acknowledges that some organizations are successfully incorporating AI into their software development processes, he points out that significant friction is prevalent, particularly in larger companies where AI-generated results are outpacing the team's capacity to assess them. He remarked, "It tends to happen in bigger companies that are 10+ years old with a higher talent variance. But it happens. A lot."