AI Code Attribution

Code as an artifact means treating the source you commit as a regenerable output of a process — the prompts, plans, and agent context that produced it — rather than the durable end product of software development. When AI agents generate most of your code, the spec and the conversation become the real artifact, and versioning must capture both the code and the process behind it. This guide explains why traditional Git falls short, how to attribute every line to AI or human, and which workflows and tools keep AI-generated code trustworthy at scale. ...

When you open a file in your project and wonder which script generated it, which AI agent wrote it, or which command produced its contents, you are facing the file lineage problem. File lineage is the practice of tracing a file back to its origin — the exact script, notebook, data source, shell command, or AI agent that created or modified it. Without this trace, teams lose visibility into how their code and data evolved, creating compliance risks, debugging nightmares, and audit failures. Emerging open-source tools like trace-file-lineage, the Agent Trace specification, and academic frameworks like PROV-AGENT now make it possible to answer this question with evidence and honest uncertainty. ...