Re_gent
Version Control for AI agent Activity
297 followers
Version Control for AI agent Activity
297 followers
Git for your AI agent’s actions. Undo, trace, and control every step. re_gent shows what your coding agent changed, which prompt caused it, and lets you roll back agent work across files and sessions.
The gap Re_gent is filling: linking file changes back to the specific agent action or prompt that caused them is something no standard version control handles. But What I'm curious about is how it handles multi-agent sessions where two agents modify the same file in sequence. Does it trace each change to the right agent independently, or does the attribution get murky
The audit trail problem with AI agents is real. When you're running agents that touch customer-facing outputs - outbound emails, content, CRM updates - knowing what ran, when, and what changed isn't nice-to-have, it becomes essential fast. Git for humans works because humans understand state. Curious how re_gent handles conflicts when two agents modify the same object in parallel - is it last-write-wins or do you surface the conflict for human resolution?
The version control framing for agent activity is interesting — most debugging of agent runs today is "read the logs and guess". Does Re_gent capture diffs at the file level or at a higher abstraction? Specifically curious whether it handles binary assets in a repo (compiled outputs, WOFF2 fonts, image exports) or focuses purely on text/code changes.
the observability gap for agent work is real and getting worse as agents do more. you end up with a codebase that changed in ways you can explain at a high level but can't trace precisely. version control for human code exists because we learned that lesson the hard way. learning it again for agent output was probably inevitable
Git for AI agents makes so much sense. The 'oops, my agent went rogue' moments are real — glad someone's solving this.