Salesforce CEO Marc Benioff said the company has almost not hired engineers over the last two years [1].
This shift signals a potential transformation in the white-collar labor market, suggesting that generative AI may permanently reduce the need for entry-level and mid-tier software development roles at major tech firms.
Benioff said the hiring freeze was due to the deployment of AI coding agents, which he said have brought "unprecedented" levels of productivity [3]. By automating routine development tasks, the company has managed to keep its engineering workforce flat while maintaining its operations as a $145 billion firm [2].
Despite the stagnation in traditional engineering roles, the company is pivoting its talent acquisition strategy. Salesforce announced plans to hire 1,000 AI-native new graduates [4]. This move suggests a preference for a new class of worker capable of managing AI systems rather than writing manual code.
To support this AI-centric infrastructure, the company is investing heavily in external technology. Benioff said the company planned to spend $300 million on Anthropic tokens [3].
While the company has largely stopped hiring traditional engineers, Benioff said that hiring has continued in other departments, specifically in sales [2]. This divergence in hiring patterns highlights a strategic shift toward revenue generation and AI management over internal software expansion.
“"almost not hired engineers"”
The Salesforce case provides a real-world example of 'AI displacement' within the tech sector. Rather than immediate mass layoffs, the company is utilizing a 'hiring freeze' to let AI absorb the growth that would typically require new human staff. This creates a bottleneck for traditional computer science graduates and accelerates the demand for 'AI-native' skills, where the primary value is no longer coding syntax but the ability to orchestrate AI agents.
