Decoding the digital age
The Existential Crisis of Software Engineers
Technology and Work
The Existential Crisis of Software Engineers
What happens when people who have spent years mastering a difficult skill discover that a machine can perform parts of it in seconds?
Software engineering has long been considered an attractive career, offering high salaries, job security and the satisfaction of building products that solve real problems for businesses and customers. But as AI becomes increasingly capable of writing code and developing software, some engineers are facing an existential crisis. They’re questioning the purpose of their roles, struggling to see a clear path for career progression and, in some cases, wondering whether they want to remain in the profession at all.
What Were All Those Years of Coding For?
Imagine spending a decade studying computer science, learning programming languages, debugging code and working your way up from a junior developer, only to watch someone with virtually no programming experience build a functioning application in minutes.
The rise of AI coding assistants and vibe coding - creating software through natural-language prompts rather than writing the code yourself - is challenging what it means to be a software engineer. Tools such as Claude Code and GitHub Copilot can generate substantial amounts of code in seconds, allowing people with limited technical knowledge to build websites, applications and working prototypes.
For engineers who have spent years mastering their craft, this raises an uncomfortable question: What was all that hard work for if almost anyone can now write software?
Of course, generating code is not the same as engineering reliable software. AI can produce convincing results while introducing security vulnerabilities, poor architectural decisions or problems that only emerge later. Human expertise remains important in testing, maintaining and understanding complex systems.
But that reassurance raises another uncomfortable question. What if AI eventually becomes good enough that human intervention is rarely necessary? And even before that happens, how much satisfaction can an experienced engineer derive from a role increasingly centred on checking work produced by a machine?
Developers’ Love-Hate Relationship with AI
According to the 2026 Stack Overflow Developer Survey, 83% of respondents use AI tools at work, with 66% using AI coding assistants or agents. Despite widespread adoption, trust remains limited: 48% said they trust AI-generated output when they can easily verify it, while just 7% trust AI with important work decisions.
Overall, 62% expressed favourable attitudes towards AI tools, although 17% cited concerns about losing their skills or training their replacement as a reason to avoid using them. The findings suggest that while AI is becoming an established part of software development, questions about its reliability and long-term impact on developers remain.
The impact on job satisfaction varies. In the same survey, around 60% of respondents said AI had improved their satisfaction with implementing code, while approximately 20% reported the opposite.
AI use among survey respondents
Source: Stack Overflow Developer Survey 2026. Different survey questions and respondent groups.
Attitudes and trust
Source: Stack Overflow Developer Survey 2026. Percentages come from separate questions; the last category is a reason for avoidance, not overall sentiment.
The Changing Rules of Career Success
For junior developers, breaking into the industry is becoming increasingly difficult. As AI takes over some of the routine coding, debugging and testing tasks traditionally assigned to less experienced engineers, companies may have less incentive to hire and train newcomers. A 2026 study by Stanford University’s Digital Economy Lab found that employment among workers aged 22-25 in AI-exposed occupations was 19% below its relative benchmark, with the gap largely driven by reduced hiring rather than layoffs. This raises a longer-term concern: if fewer junior engineers are hired, how will the next generation gain the experience needed to become senior developers?
For senior engineers, AI is creating a different kind of career uncertainty. A 2025 BairesDev survey found that 65% of senior developers expected their roles to be redefined in 2026, with growing emphasis on system architecture, technical strategy and overseeing AI-generated code. As AI takes over more routine programming tasks, experienced engineers may be expected to spend less time writing code and more time designing complex systems, integrating AI-generated work, addressing security risks and making broader technical decisions. For those who have built their careers around hands-on programming, this shift could make career progression more challenging, as advancing may increasingly depend on overseeing AI-generated work rather than writing code themselves.
When AI Becomes Mentally Exhausting
The rapid adoption of AI may also be taking a toll on developers’ mental health. Beyond fears of losing their jobs, some engineers describe feeling overwhelmed by constantly changing tools, the pressure to keep up with an industry that seems to be moving faster than ever, and the increasingly draining experience of using AI in software development.
In September 2026, Futurism reported on a software engineer who described working at a large company where developers were increasingly reliant on Claude Code. Despite generating code faster, development remained slow, with employees reportedly working 12-13-hour days "just to press enter". The engineer described colleagues across all seniority levels spending their days prompting AI rather than solving problems themselves, leaving them with little sense of accomplishment. The experience, they said, was "so soul-sucking."
Reviewing AI-generated code can also be mentally exhausting. As one Quora contributor puts it, imagine being an inspector asked to examine an entire house that appeared overnight. You weren’t involved in building it, but you’re still responsible for identifying everything that might be wrong. Similarly, developers may find themselves reviewing hundreds of lines of AI-generated code without having followed the decisions behind them, making it difficult to understand the system as a whole.
Researchers have also begun examining a phenomenon known as AI brain fry. A study by Boston Consulting Group involving nearly 1,500 workers found that 14% reported cognitive overload associated with intensive AI use. The problem appears particularly relevant to developers managing multiple AI agents, where faster output can mean more decisions, interruptions and work to review.
Beyond Productivity
AI is becoming an essential tool in software development, helping engineers work faster and automate repetitive tasks. But its impact goes far beyond productivity. The pressure to keep up with rapidly evolving technology, adapt to changing responsibilities and constantly prove their value is creating new sources of stress. Even the process of working with AI can be mentally exhausting, with developers spending hours reviewing generated code, managing AI agents and making decisions at an increasingly rapid pace.
Software engineering is unlikely to disappear, but the psychological impact of this transition deserves more attention. For engineers who have spent years building their careers around programming, the uncertainty can be deeply personal. Losing confidence in their skills, feeling overwhelmed by new expectations or no longer enjoying work they once loved can take a toll on their mental well-being. As AI becomes more deeply embedded in software development, the question is how engineers can adapt without sacrificing their sense of purpose and mental health in the process.
