A developer scrolls through their GitHub commit history this week and notices something unfamiliar. Beside their own name, a second identity has appeared: Copilot. The code was generated in their editor, accepted with a keystroke, and pushed to the repository, but the record no longer claims sole authorship. What previously felt like a private collaboration between a human and a machine is now a matter of public record.

The Mechanics of AI Attribution

Visual Studio Code has introduced a fundamental shift in how AI contributions are tracked by enabling Git AI co-authoring by default for specific workflows. This feature specifically targets interactions within Copilot Chat and the agentic mode, where the AI autonomously plans and executes code modifications. When Copilot modifies a file under these conditions, the editor automatically appends the AI as a co-author to the resulting Git commit.

Developers can manage this behavior through a new configuration setting called `git.addAICoAuthor`. The system provides three distinct levels of attribution to suit different team standards and personal preferences. The default setting, `chatAndAgent`, ensures that co-author metadata is added only when code is generated via the chat interface or through agent-led workflows. For those seeking total transparency, the `all` setting expands this attribution to every single AI-generated snippet, including the subtle, line-by-line suggestions provided by inline autocomplete. Conversely, setting this value to `off` completely removes the AI co-author trailer from the commit message, returning the repository to a human-only attribution model. Detailed technical specifications for this implementation are available in the official update documentation.

From Ghostwriting to Software Provenance

For the past few years, the relationship between a developer and an AI assistant has mirrored that of a writer and a ghostwriter. A developer would accept a suggestion, and the resulting code would be attributed entirely to the human, regardless of whether the AI wrote one line or one thousand. This created a gap in the historical record of the software, where the actual origin of the logic was obscured by the act of acceptance. By introducing formal co-authorship, VS Code is moving the conversation from simple productivity to the realm of software provenance—the ability to trace the origin and evolution of every line of code in a system.

This shift introduces a critical distinction between different types of AI assistance. Under the `all` configuration, the record becomes a granular map of human versus machine input, revealing exactly where the AI filled in the blanks. Under the `chatAndAgent` configuration, the attribution serves as a marker for structural changes, highlighting where the AI acted as an architect rather than a typist. This allows teams to analyze the nature of their technical debt and the reliability of their codebase by identifying which sections were driven by AI-led planning. The tension is no longer about whether AI is being used, but about how much of the intellectual heavy lifting is being delegated to the model.

Code is evolving from a solo performance into a documented collaboration between diverse forms of intelligence.