Git-History Pipeline Helps Developers Document Legacy Code Using AI Drafts

A developer workflow has emerged to tackle the challenge of documenting legacy codebases where the reasoning behind old code is lost to time. The approach uses a Python script to extract git history, blame data, and code markers into a structured context pack, giving AI models evidence-based material rather than letting them fabricate rationale. The method distinguishes between what an AI model may draft—such as API surfaces and changelog narratives—and what humans must verify, including security statements and the intent behind unexplained constants. A key principle of the pipeline is that every AI-generated claim must cite a specific commit hash, preventing the model from silently inventing explanations. The workflow positions AI as a drafting assistant while keeping human accountability intact for anything where an incorrect statement could cause undetected harm.