Human vs. AI – Diff-based line-level provenance for text under agentic editing
This article introduces a tool for tracking line-level provenance in text edited by AI agents. It aims to distinguish between human-authored content and machine-generated 'slop' to maintain control over code and documentation.
Why it matters
As AI-assisted coding becomes standard, maintaining human oversight and intellectual ownership of software projects is becoming a critical technical challenge.
Line-level provenance for text under agentic editing — who wrote this line, us or them? — derived from a text's version history. Use it as library or as CLI tool.
With agentic coding and editing, provenance becomes a pertinent question. Text a human wrote or edited should be considered close to sacred: an agent should be hesitant and have a very good reason to touch it. Slop another agent has produced, on the other hand, is completely up for grabs.
A use case for this: Take a mostly vibecoded app in which you want to establish some corners in the code where you want to assert your ideas and ownership. You surely don't want another agent bulldoze over this piece of code in the next session.
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