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Treat AI evaluation criteria as code for better management

Evaluation criteria for AI models should be treated as code and versioned accordingly. This approach ensures that changes and potential rot in these criteria are tracked and managed, preventing issues like the three-month unnoticed decay of a judge prompt mentioned in the article. By applying software engineering principles to evaluation, developers can maintain more robust and reliable AI systems. AI

IMPACT Adopting code-like versioning for AI evaluation criteria can improve model reliability and reduce the risk of undetected performance degradation.

RANK_REASON The article discusses best practices for managing AI evaluation criteria, framing it as an opinion piece on software engineering principles applied to AI.

Read on Medium — MLOps tag →

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  1. Medium — MLOps tag TIER_1 English(EN) · Ethan Walker ·

    Your eval criteria are code. Version them like code.

    <div class="medium-feed-item"><p class="medium-feed-snippet">A judge prompt is an implementation. The criterion it encodes is a contract, and ours rotted for three months before anyone noticed.</p><p class="medium-feed-link"><a href="https://medium.com/@ethan-writes-AI/your-eval-…