Evaluation Fallback Path

機械支援の翻訳下書き (Japanese) for "Evaluation Fallback Path": Evaluation Fallback Path is a ai resilience pattern that keeps an AI feature useful when a provider or tool is unavailable for AI quality and safety testing. It uses degraded states, deterministic responses, and operator notices so teams can avoid fake AI success while keeping evidence, reliability, and public-safe operational boundaries clear.

“例文の下書き: The AI platform team used Evaluation Fallback Path when a release candidate failed a reasoning scenario, so the team could avoid fake AI success before the agent workflow reached production.”