Former Meta executive warns most engineers risk falling behind in AI revolution

A former Meta engineering manager has warned that only a tiny share of software developers are truly benefiting from the artificial intelligence revolution, while the vast majority risk being left behind.

Kun Chen, who previously held engineering roles at Meta, Microsoft and Atlassian, said just around 2% of engineers are using AI in a way that delivers major productivity gains.

According to him, these workers have mastered what he describes as “agentic engineering” — a more advanced approach that allows AI systems to handle larger parts of coding, testing and workflow execution.

Chen said most companies are seeing only modest productivity improvements of around 10% to 15% because the majority of employees still use AI tools in a limited or superficial manner.

He explained that chief technology officers are increasingly noticing a divide between a small number of highly efficient AI-powered engineers and larger teams that continue to move slowly on routine tasks.

According to Chen, the most important and high-impact projects are now being redirected toward this top-performing minority, as businesses recognise they can execute work significantly faster with fewer people.

He warned that this shift could have serious implications for traditional engineering teams, particularly as major technology firms continue to cut jobs, restructure departments and focus on leaner operations.

Chen argued that the AI transition resembles previous industrial and internet-era disruptions, where early adopters initially represented a small minority before fundamentally reshaping the workforce.

Rather than focusing too heavily on mastering individual AI tools that may quickly become outdated, he advised developers to build a mindset of continuous learning and rapid adaptation.

His comments come amid growing pressure across the tech industry, where companies are increasingly rewarding employees who can integrate AI deeply into their daily work while questioning the need for larger slower-moving teams.