The Evolving Value of Software Engineers in the AI Era
In a rapidly transforming tech landscape, software engineers who successfully blend traditional coding expertise with AI tool proficiency are becoming increasingly valuable assets to their organizations. According to a new report by Seattle-based technical talent evaluation startup Karat, AI is dramatically reshaping the software development field – boosting overall productivity by 34% on average while simultaneously widening the gap between top-performing and underperforming engineers. These insights emerge from Karat’s comprehensive “AI Workforce Transformation” report, which surveyed 400 engineering leaders across the United States, India, and China to understand how artificial intelligence is revolutionizing software development practices and reshaping the technical workforce.
The findings paint a stark picture of growing value disparity among engineers in the AI era. A remarkable 73% of engineering leaders now believe that a strong engineer is worth at least three times their total compensation – highlighting the premium placed on exceptional talent. Conversely, 59% of leaders report that weaker engineers deliver zero or even negative value as AI tools become more integrated into development workflows. This widening performance gap emphasizes how AI is acting as a talent multiplier for those who can effectively harness its capabilities. The report identifies code generation (used by 83% of engineers) and testing/QA/code review (61%) as the most common AI applications in daily engineering work, with autonomous engineering agents emerging as the AI technology offering the highest return on investment according to most leaders.
Despite ongoing cost pressures and high-profile layoffs at major tech companies like Amazon and Microsoft, the report offers some reassurance about the future of engineering jobs. A significant 85% of engineering leaders expect their engineering headcounts to remain flat or increase over the next three years, suggesting that AI isn’t driving widespread job elimination in the near term. However, the nature of engineering roles is clearly evolving. Beyond traditional skills like problem-solving, communication, and product understanding, engineers now need proficiency in AI-native abilities such as working with agentic AI, using AI for coding tasks, integrating third-party AI APIs, mastering prompt engineering, and understanding how to evaluate and mitigate AI-related risks. This evolution in required skills is reshaping how companies need to evaluate and hire technical talent.
The changing landscape is perhaps best illustrated by comments from Amazon AWS executive Colleen Aubrey, who recently suggested that agentic AI teammates should now be considered “as essential as the people sitting right next to you.” This perspective represents a significant shift from viewing AI tools as mere productivity enhancers to seeing them as collaborative partners in the development process. It also aligns with Karat’s finding that nearly 70% of engineering leaders plan to strengthen their AI capabilities through strategic hiring practices. However, there appears to be a disconnect in how companies are adapting their hiring processes, as almost two-thirds still prohibit AI use during interviews, and fewer than 30% are updating their assessments or training interviewers to identify AI-ready talent.
To address this gap, Karat has launched its NextGen talent evaluation platform alongside the report. The platform features a human-plus-AI interview format where candidates work on complex, multi-file projects with an integrated AI assistant while collaborating with Karat’s expert interviewers. This approach aims to evaluate not just coding ability but also how engineers reason through problems, make trade-offs, and exercise judgment when working with AI tools. DocuSign CTO Sagnik Nandy, a Karat customer, emphasized that while AI is transforming engineering, “the real breakthroughs happen when human judgment and AI capabilities work together,” and that assessing this combination reliably has been the missing piece in talent evaluation. This perspective highlights the emerging consensus that the future belongs to engineers who can effectively collaborate with AI rather than those who merely rely on traditional coding skills.
Founded in 2014 by Mo Bhende and Jeff Spector, Karat has established itself as one of Seattle’s highest-valued startups, achieving unicorn status after raising $110 million in a Series C funding round in 2021, which brought its valuation to $1.1 billion. With total funding of $151.6 million to date, the company now ranks 15th on GeekWire’s list of top startups in the Pacific Northwest. As the software development industry continues to navigate the complex integration of AI into its workflows and talent evaluation processes, companies like Karat are positioning themselves at the forefront of helping organizations identify and nurture the kind of hybrid human-AI engineering talent that will define the next generation of technical innovation. The message is clear: in tomorrow’s engineering workforce, the most valuable players will be those who can harness AI as a partner rather than see it as a replacement.
