LLM Eval for Cold Email

LLM eval for cold email is a systematic quality check applied to every AI-generated cold email before it reaches a prospect. The eval combines automated rule checks (word count, banned phrases, format) with LLM-as-judge scoring (tone, relevance, naturalness) and human spot-checks. The output is a pass/fail decision per email plus a quality score that tracks agent performance over time.

The principle: a cold email eval should mirror what a skilled SDR manager would check in a 15-second review. Is it short? Is it relevant? Does it sound human? Is the signal real? Is the ask appropriate? Codify that review into automated + LLM + human layers.

The 3-Layer Eval

Layer 1: Automated rule checks (every email, instant)