The New Git Blame: Who's Responsible When AI Writes the Code?

git blame used to be simple.
It told you who wrote a line of code—and maybe, if you squinted at the commit message, why.

But now? That line might’ve been written by GPT-4. Or Claude. Or merged automatically by a bot you forgot existed.

And when something breaks in production, no one’s quite sure who’s on the hook.

We’re entering a new era of software development—where authorship, responsibility, and accountability are getting harder to untangle.

🚨 Claude Tried to Co-Author My Commit

Let’s start with a real example.

Claude Code, Anthropic’s AI coding assistant, automatically adds itself as a co-author on any commit it helps generate:

Co-authored-by: Claude <noreply@anthropic.com>

You don’t ask it to. It just does it by default.

And for a while, that email address wasn’t registered to Anthropic on GitHub. So in some public repos, Claude commits showed up as authored by a completely unrelated user—someone who had claimed that address first.

So now your commit history says:

“This line was written by Claude… and also Panchajanya1999?”

Even if the attribution worked, Claude still provides:

• No prompt history
• No reviewer
• No model version
• No audit trail

If that line breaks production, good luck tracing it back to anything useful.

⚙️ If you’re using Claude, disable this by setting:
includeCoAuthoredBy: false in your Claude config.

But the bigger issue? This is what happens when AI tries to act like a teammate—without any of the structure real teammates require.

🧠 When Git Blame Isn’t Enough

Claude isn’t the only case. Here’s how authorship is already breaking in modern, AI-powered workflows:

👥 Developers Are Reframing AI Responsibility

Teams are starting to adopt new mental models:

• 🛠 AI as a tool → You used it, you own the result.
• 👶 AI as a junior dev → It drafts, you supervise.
• 🤖 AI as an agent → It acts independently, so policy and traceability matter.
• 👥 AI as a teammate → It commits code? Then it needs review, metadata, and accountability.

One lightweight approach:
Bot Sponsorship — any AI-authored or reviewed PR must have a named human who takes responsibility.

🛠 Making AI-Assisted Development Accountable

Here are a few things teams are doing to keep ownership clear and prevent surprise postmortems:

1. Annotate commits and PRs clearly

git commit -m "Refactor auth logic [AI]"
Co-authored-by: GPT-4o <noreply@openai.com>
Reviewed-by: @tech-lead

In PR descriptions:

### AI Involvement
Model: Claude 3
Prompt: "Simplify caching layer"
Prompted by: @victoria-dev
Reviewed by: @tech-lead

2. Store lightweight metadata

ai_contribution:
  model: gpt-4o
  prompted_by: victoria
  reviewed_by: tech-lead
  model_version: 4o-2025-06

This makes it way easier to debug or explain later.

3. Treat bots like teammates (with guardrails)

• Don’t auto-merge bot PRs
• Require human signoff
• Keep prompt + model logs for important changes

🧾 Why It Actually Matters

This isn’t just a Git trivia problem. It’s about:

• 🪵 Debugging — Who changed what, and why?
• 🛡 Accountability — Who’s responsible if it breaks?
• 📋 Compliance — In fintech, healthtech, or enterprise software, this stuff has legal consequences

Even in small teams, having unclear authorship leads to tech debt, confusion, and wasted time later.

💬 What About Your Team?

If you’re using Claude, Copilot, Cursor, or any AI tools:

• Do you annotate AI-generated code?
• Do bots ever open or merge PRs?
• Have you had to debug a “ghost commit” yet?

Drop a comment — I’m working on a follow-up post with real-world policies and would love to hear what’s working (or not) on your end.