More developers than ever are relying on agents to do their work for them.
A recent survey of 450 US software engineers from CodeSignal found that 91% reported using agentic AI coding tools, such as Claude Code, Codex and Cursor in their day-to-day work. Additionally, more than three-quarters of those engineers shipped AI-generated code into production over the past six months.
The data adds to the broader narrative that the role of an engineer is transforming as their task load shifts from software coder to AI orchestrator. And despite fears that AI will kill the jobs of software engineers, job postings for developers are up year-over-year as novice-led vibe coding brings about the dawn of custom software that requires more in-house expertise.
“Software development has fundamentally changed,” said Tigran Sloyan, co-founder and CEO of CodeSignal. “Engineers are no longer coding alone; they’re working with AI agents, and the best ones know how to get the most out of them.”
It’s why, for engineers, AI skills may become non-negotiable. According to CodeSignal’s survey, 73% of engineers reported that not adopting these tools puts them at risk of becoming less competitive, and 42% reported that they’d be hesitant to hire or work with a developer who doesn’t use them.
And as these skills become more in demand, CodeSignal debuted agentic coding assessments designed to test engineers’ AI readiness. These assessments test whether engineers can use agentic tools to build working solutions and explain their technical decisions to reviewers, rather than simply testing if they can build algorithms or write code by hand.
“The companies that figure out how to hire for—and develop—those skills will have a real advantage,” Tigran said.
And one thing is clear: AI coding tools are accelerating development time and driving down the cost of building software. That's increasing, rather than decreasing, the need for organizations to hire more developers to connect the dots and manage the code.
Our Deeper View
As these models become increasingly powerful, demand for AI skills, is also rising quickly. The problem, however, is the limited resources by which developers can learn how to leverage these tools. Modern curricula at universities can’t always keep up with the pace of change, and reskilling is becoming more popular than ever. It’s the sentiment that drives some of AI’s leaders to tell young people to abandon college altogether and just start building. Case in point: OpenAI CEO Sam Altman told an attendee at a January Town Hall meeting that for AI builders, it’s “probably not the best use of your time to be in university right now.” The question remains, in the face of such a monumental shift, whether universities and educators will be able to make the shift, too.