What is the core problem with AI agent auditability?

AI agents have write access to codebases but git only records the file change, not which agent made it, which prompt triggered it, or what the agent intended.

What does re_gent do?

re_gent stores AI agent session state in a .regent directory alongside .git. It tracks which prompt produced each change, lets you blame by agent, and supports rollback of agent activity.

How much traction does the Show HN: Git for AI Agents post have?

129 HN points and 87 comments. re_gent itself has 498 GitHub stars and 127 Product Hunt upvotes.

Is this a wide open gap or competitive?

Wide open. re_gent, regent-vcs, and Origin are all early-stage with no dominant player. Git has no native concept of AI agent authorship.

What does git blame look like for AI agents?

Origin tags every commit with which AI model wrote it, what prompt generated it, and what it cost. The origin blame command shows [AI] or [HU] per line like git blame but for AI agents.

← Back to dashboard

clawsmith.com/signal/ai-agent-version-control-blame-audit-trail

⚠ IssueWide Opendev_tool_cliLive

AI coding agents have write access to your codebase but no audit trail for which agent made each change and which prompt caused it

When something breaks in AI-assisted development, developers cannot answer which agent wrote this, which prompt caused it, or how to rewind. re_gent (498 GitHub stars, Product Hunt launch) addresses this by storing agent session state in .regent alongside .git. Show HN: Git for AI Agents got 129 pts and 87 comments on HN. Multiple tools launched in 2026: Origin, re_gent, regent-vcs all targeting the same gap.

Product Idea from this Signal

A CLI tool that records which AI agent wrote each code change and why

874 ▲

When multiple AI coding agents (Cursor, Copilot, Claude Code, Devin, aider) touch a codebase, there is no way to know which agent made which change, what prompt drove it, or why a decision was made. Developers lose accountability at the commit level and cannot audit, rollback, or blame AI-authored changes with any more precision than a co-author tag. This tool wraps the version control layer with per-change agent attribution, prompt capture, and a queryable audit log.

developer-toolsai-agentsversion-controlaudit-trailgitattributioncompliance

Competitive48 leadsView Opportunity →

Score Breakdown

GitHub

531

216

127

Social Proof 3 sources

regent-vcs/re_gent – Version-Control for AI coding agents

gh:regent-vcs · 4/10/2026

531 HN

Show HN: Git for AI Agents

doshay · 5/7/2026

216 PH

Re_gent – Version Control for AI agent Activity

re_gent · 4/10/2026

127

Existing Solutions 2 competitors

re_gent498 GitHub stars, 127 PH upvotes

Version control for AI agent activity, tracks sessions in .regent alongside .git

OriginEarly stage, minimal HN traction

Git blame for AI agents, tags every commit with which AI wrote it

Gap Assessment

Wide OpenNo dedicated solution exists

re_gent (498 stars), regent-vcs, and Origin are all early-stage with no dominant player; Git natively has no concept of AI agent authorship; gap is wide open.

Frequently Asked Questions

Virality Score

874

across 0 platforms

Details

Signalissue

Ecosystemdev_tool_cli

Sources3

Platforms0

Updatedunknown

Trend→ stable

Top ideas

All ideas →

0A mobile app that saves articles fully offline with a one-time purchase and no cloud subscription 0A CLI tool that benchmarks AI coding agents against a team's own real production tasks and codebase 0An MCP server that gives AI agents a production-grade browser session with built-in anti-bot bypass, CAPTCHA resolution, and stateful session recovery

Related signals

All signals →

1.1KGit Doesn't Track AI Agent Reasoning — Devs Building Dedicated Audit-Trail VCS for Agents