Do you trust AI in Testing?
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A testing practitioner shares poll data showing that 57% of developers still don't trust AI enough to use it in production workloads, despite management pressure to adopt AI-powered testing. The author proposes a 'TRUST framework' with five evaluation dimensions for AI agent responses: Truthfulness, Relevance, Understanding, Safety, and Transparency. The framework moves beyond binary pass/fail results, assigning scores across each dimension to better evaluate non-deterministic LLM outputs. Three example responses (good, warning, bad) are walked through the evaluator, highlighting how a convincing-sounding but inaccurate AI response can slip through without multi-dimensional evaluation. Feedback is solicited from the community.