You’re standardizing a prompt library for Microsoft 365 Copilot across Finance and HR, and both groups require separation of duties for production…

An automated prompt regression gate is the best solution. It enforces a standardized, repeatable quality check before any change is promoted to production. This approach is fast, fitting within a strict change window, and generates an immutable audit trail of test results, proving quality improvements over time. It meets the requirements for separation of duties and auditability without requiring new connectors or custom application code, as the validation happens within the CI/CD pipeline.

B. Increasing temperature is a model parameter adjustment for creativity, not a validation process for ensuring prompt quality or compliance.

C. Manual stakeholder review is not scalable, is prone to human error, and cannot consistently meet a strict, short change window.

D. Releasing to production and monitoring complaints is a reactive approach that fails the core requirement of validating before promotion.

1. Microsoft Azure DevOps Documentation, "Release deployment control using gates." This documentation details how automated gates can be used in a release pipeline to enforce quality policies before promotion, which is directly applicable to managing prompt libraries.

2. Microsoft, "LLMOps: The Foundation of Effective AI-Powered Application Development," (2023). This paper discusses the importance of automated testing and validation in the LLMOps lifecycle to ensure reliability and quality of generative AI applications. Section: "Automated Testing and Validation."

3. Microsoft Azure Machine Learning Documentation, "What is prompt flow?". Prompt flow includes capabilities for large-scale testing and evaluation, which can be integrated into a CI/CD pipeline to serve as an automated regression gate.