The Battle Over the Commit Message: Disclosure or Advertising?

The Git commit message has long been a sacred space for technical documentation—a concise record of what changed and why. However, a new trend has emerged: the inclusion of automated attribution tags like "Assisted by blabot" or "Co-authored-by: Claude". While some developers view this as transparency, others see it as a corporate land grab for free advertising space within the version control history of open-source projects.

This debate touches on more than just aesthetics; it raises fundamental questions about the nature of AI tools, the legalities of copyright, and the professional responsibility of the developer.

The Case Against "Commit Advertising"

The core argument against AI attribution in commits is that these tags serve as free advertisements for multi-billion dollar companies. As noted by developer Akseli Lahtinen, many of these tools are subscription-based, meaning developers are paying for the privilege of then providing the company with free marketing in their public repositories.

Beyond the marketing aspect, there is a strong argument regarding the purpose of the commit history. Commits are intended for technical information. Adding "sent from my iPhone" or "generated by GPT-4" adds noise to the history without providing technical value. For those who believe in disclosure, the suggestion is to move these notes to the Merge Request (MR) or Pull Request (PR) level, where the context of the work is discussed, rather than baking the advertisement into the permanent git log.

Tool vs. Co-Author: A Philosophical Divide

One of the most contentious points in this discussion is the use of the Co-authored-by trailer. Traditionally used for pair programming between humans, its adoption by AI tools suggests a shift in how we perceive LLMs.

The "Tool" Perspective

Many argue that an LLM is a tool, not a collaborator. As one community member pointed out:

When you make a design with Photoshop or InDesign, it's not "co-designed by Photoshop," it's just a tool and you used the filters it provides.

From this perspective, calling an AI a "co-author" is a category error. It frames the relationship as a partnership rather than a user utilizing a sophisticated utility.

The "Disclosure" Perspective

Conversely, some developers argue that knowing a piece of code was AI-generated is a critical signal. It can alert reviewers to be more skeptical of the logic or warn future maintainers that the code might not have been deeply considered by a human. In this view, the Co-authored-by tag is a necessary disclosure for the sake of code quality and accountability.

The Hidden Incentives: Metrics and Copyright

While the debate often focuses on the developer's experience, there are systemic incentives at play that make these tags attractive to corporations.

Corporate Metrics

Some organizations now use these tags to track "AI adoption." By scanning commit histories for known AI agent trailers, management can generate dashboards showing what percentage of the codebase is being produced via AI. In this scenario, the "ad" isn't for the public—it's a telemetry beacon for corporate oversight.

The Copyright Trojan Horse

There is also a legal dimension to this trend. In many jurisdictions, AI-generated content is not copyrightable. Some argue that by pushing the "Co-authored-by" narrative, AI labs are attempting to blur the line between human and machine contribution.

"Co-authored by AI model" is a nonsense that AI labs are pushing everywhere because they definitely want the copyright rules to change... so they can still claim that the IP is theirs.

By intertwining human and AI commits, it becomes significantly harder to decouple the two, potentially creating a legal gray area that benefits the tool providers over the individual contributors.

Finding a Middle Ground

If disclosure is the goal, but advertising is the enemy, how should developers handle AI attribution?

1. Use Generic Disclosures: Instead of naming a specific product (e.g., "Claude"), use a generic term like "Generated by an LLM."
2. Custom Trailers: Utilize Git's interpret-trailers to create custom, non-branded tags that provide the necessary technical context without the marketing fluff.
3. PR-Level Disclosure: Keep the permanent git log clean by disclosing AI assistance in the Pull Request description, which provides the context of the change without cluttering the long-term history.
4. Opt-in, Not Default: The primary frustration stems from tools that enable these tags by default. The industry standard should shift toward an opt-in model where the developer consciously chooses how—or if—they wish to attribute their tools.