PromptOps — LLM Prompt Version Control Platform

Git for AI prompts — version, test, and rollback LLM changes before they break production

PromptOps brings software engineering discipline to LLM prompt management with Git-like version control, automated A/B testing across production traffic, and regression detection that catches prompt degradation before users do. Built on PostgreSQL DAG structures and ClickHouse metrics streaming, teams can safely iterate on prompts across staging and production environments with one-click rollbacks when GPT-4 updates silently break your carefully tuned instructions.

Key Benefits:

- Git-like branching and merging for prompt experiments with full audit trails showing exactly who changed what prompt when

- Automated regression detection using ClickHouse to stream response quality metrics and trigger rollbacks when accuracy drops below thresholds

- Traffic-split A/B testing framework that routes 10% to experimental prompts while keeping 90% on stable versions, preventing full production failures

MVP Scope: Core prompt versioning with Git-like DAG structure, basic A/B testing with traffic splitting, automated regression detection on key metrics, deployment to staging/production environments, and real-time monitoring dashboard for prompt performance across LLM endpoints.

Tech Stack: PostgreSQL, Redis, ClickHouse, S3/Object Storage, Python, libgit2, FastAPI, React

Components:

- Prompt Repository Engine with Git-like version control

- A/B Testing Framework with traffic splitting

- Regression Detection Engine with automated rollback

- Multi-environment Deployment Manager

- Monitoring & Alerting Dashboard

Quality assessment: Strong concept addressing a genuine pain point (prompt management in production LLM systems) with concrete technical architecture (Git DAG + ClickHouse metrics + A/B testing), but lacks originality depth—prompt versioning tools already exist (Weights & Biases, Langsmith)—and the pitch cuts off before demonstrating differentiation or market validation.