Clay's Everett Berry breaks down how elite revenue teams are actually winning with AI today. We cover the GTM Engineer model Clay runs in-house, why prompt iteration and "taste" still matter, and the unsexy but vital work of segmentation, account scoring, and orchestration across the funnel. Plus, where AI SDR efforts go off the rails, and the concrete first steps a CRO should take to get real adoption and lift.
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Timestamps:
(01:16) — Guest intro: Everett Berry, Head of GTM Engineering at Clay
(02:09) — Origin story → growth roles → discovering Clay
(04:52) — What is a GTM Engineer? Clay's embedded (Palantir-style) model & why it works
(08:10) — Automating the busywork: pre-call research & more
(10:53) — Why many AI GTM pilots miss ROI, plus AI-SDR hype
(17:01) — Agent scope and lossiness, checks/evals, and prompt iteration best practices
(24:20) — Day-1 win: industry classification; when to use GPT vs. Anthropic for the job
(27:54) — CRO AI rollout sequence
(33:32) — Data foundations: pipelines, API realities, and org readiness
(41:25) — Org design: where GTM Engineering lives
(52:10) — Team & stage: roles to hire, GTME + RevOps + agency model; what to insource vs. outsource
(1:00:24) — Rapid fire questions
