Google has issued strict new internal guidelines requiring its software engineers to use only the company’s proprietary AI models for all coding-related tasks.
The directive, communicated via internal emails and reinforced during company-wide meetings, marks a significant shift in how Google expects its technical workforce to operate in the age of AI.
Engineers must now rely exclusively on in-house tools such as Cider and Gemini for Google—formerly known as Goose—for software development.
Use of third-party AI tools for coding is prohibited unless explicitly approved by management.
This move is part of a broader strategy to consolidate AI usage within Google’s ecosystem, enhance data security, and drive productivity gains without increasing headcount.
AI Proficiency Now a Core Expectation at Google
The mandate is not limited to tool usage. Google has also introduced performance expectations around AI proficiency.
Managers are reportedly asking engineers to demonstrate daily AI usage.
Although not yet part of formal performance reviews, many employees believe this will influence their career progression.
Updated job descriptions for engineering roles now explicitly mention AI-powered problem-solving as a core competency.
Employees are encouraged to build workflows that incorporate AI tools and benefit broader teams—efforts that are being informally rewarded.
In an internal meeting, CEO Sundar Pichai emphasized the need to “accomplish more by taking advantage of this transition,” describing the current phase as one of “extraordinary investment” in AI.
Internal Tools Take Center Stage
Google’s internal development platform, Cider, is central to this transition.
It features coding agents powered by Gemini AI, trained on Google’s proprietary technical data.
These tools are designed to assist with code generation, debugging, and optimization, tailored specifically for Google’s infrastructure.
To support adoption, Google launched “AI Savvy Google,” a curated learning platform offering toolkits, training sessions, and product-specific resources.
A collaborative program with DeepMind—called “Building with Gemini”—has also been introduced to upskill engineers in advanced AI capabilities.
Teams in legal, sales, and operations are being encouraged to use AI tools like NotebookLM.
Some employees in these functions are also developing custom Gemini models tailored to their roles.
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