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A plain-language, source-backed guide to LLM evaluations: how to build repeatable eval loops with inputs, gold answers, and graders, why unchecked judge models are the most common way AI teams fool themselves, and how to get honest numbers with error bars for code-based and model-based grading of retrieval and agent systems.