System Prompt Version Control — Safely Manage Prompt Changes

I will build a system prompt version control and deployment system — enabling your team to develop prompt changes in a staging environment, run evaluation tests before production deployment, roll back to previous versions when changes cause quality regression, and maintain a complete changelog of every prompt modification with its performance impact. System prompts deployed without version control and evaluation testing create unpredictable production behaviour — a prompt change that improves one aspect of AI behaviour while degrading another is invisible without systematic evaluation, and without version control there is no clean rollback path when a change causes production issues.

The system covers a prompt versioning repository (Git-based), staging environment for testing prompt candidates, an evaluation suite running on each candidate, deployment approval workflow, production deployment with instant rollback, and a prompt changelog with performance metrics.