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Nightly Prompt Drift Checks Can Catch Silent AI Behavior Changes at No Cost

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Prompt drift occurs when small edits to an AI system prompt gradually alter model behavior in tone, structure, or safety compliance without triggering any error logs or CI failures. Unlike hard crashes, drift manifests subtly — such as dropped disclaimers, shifted response style, or increased agreeableness to unsafe inputs — making it invisible to standard code review. A practical mitigation is a nightly automated script that runs fixed probe inputs against the current prompt and scores outputs using a saved baseline. The script uses any OpenAI-compatible API endpoint, keeping it vendor-agnostic, while free-tier model access can reduce the running cost to zero. The workflow captures a one-time baseline and flags average score drops each night, enabling teams to detect behavioral regression before it reaches end users.

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Nightly Prompt Drift Checks Can Catch Silent AI Behavior Changes at No Cost · ShortSingh