Google has issued a bold new directive: software engineers must now rely solely on its internal AI tools when writing code. This policy shift is part of CEO Sundar Pichai’s push to ensure every employee not only adopts AI but also demonstrates proficiency—both to drive efficiency and influence career growth.
In June, Engineering Vice President Megan Kacholia emailed all software engineers, emphasizing the use of Google’s internal AI systems for development tasks. Any use of third-party AI tools—even for non-coding tasks—now requires explicit approval, reinforcing internal AI tools as the default for all development activities.
At a subsequent all-hands meeting in July, Sundar Pichai reiterated this push: embracing AI is essential for Google to remain competitive in today’s tech race.
Insiders describe a workplace where daily AI usage is no longer optional. Performance reviews now consider how actively engineers apply AI, and those who develop AI-powered workflows that benefit their teams may earn special recognition. As one engineer put it: “It seems like a no-brainer that you need to be using it to get ahead.”
Despite the apparent influence of AI proficiency on promotions and evaluations, Google maintains that it’s not formally part of reviews. Still, the message is unmistakable—AI fluency is increasingly crucial.
Google is scaling internal AI infrastructure to support this directive. For coding, it provides tools like Cider—a platform using internal models including “Gemini for Google,” specifically trained on the company’s technical knowledge. Across other departments—from sales to legal—employees are being encouraged to use tools like NotebookLM. Some are even training tailored versions of Gemini for specialized roles.
Google’s commitment to advancing “agentic coding” is further underscored by a recent strategic hire—acquiring CEO Varun Mohan and other talent from AI-code startup Windsurf in a $2.4 billion acquisition.
Google’s mandate echoes a broader trend: tech giants are embedding AI deeply into operations, hoping to unlock efficiency and stay ahead. At Google, over 30% of newly written code now originates from AI—up from 25% just months ago—highlighting a rapid shift toward automation.