Episode

15 Oct 2025 · 50 min

0:00

In this Revenue Leadership Podcast episode, host Kyle Norton interviews Everett Berry, Head of GTM Engineering at Clay, in an AI‑focused Q&A format. The conversation begins with an overview of Clay’s GTM engineering organization, distinguishing between forward‑deployed GTM engineers who work directly with customers and an internal GTM engineering team that builds and maintains automation for all GTM motions. Everett explains the core tech stack—Clay, Snowflake, Salesforce, Gong, and a Slack app—and how the internal team bundles data from these sources to generate Google Slides decks, QBRs, and other sales assets. The discussion moves to how the GTM engineering team reports to the co‑founder/Head of Ops, its interaction with RevOps and finance, and the matrix‑style responsibility for pipeline and growth targets. Everett then details the third‑party AI tools Clay evaluates or uses, including Dust (an internal‑knowledge agent), Crosby (AI‑driven legal redlining), Granola (call‑transcript formatting), and Gong Engage’s new API for sequencing. He highlights popular internal use cases such as automated content creation (Google Docs/Slides from call transcripts) and the nascent native sequencer, noting its current suitability for low‑volume, ops‑driven outreach. The hosts explore broader market trends: the potential for a single “pane of glass” sales stack that unifies call recording, sequencing, and CRM, the emerging importance of DM‑based selling (iMessage, WhatsApp, Slack), and the lack of robust tools for text‑based outreach. They debate AI’s impact on sales roles, suggesting a bifurcation where top‑performing reps become more valuable while low‑skill grinders face pressure, and they envision smaller, highly productive AI‑enabled companies. Everett offers practical advice on when to hire a GTM engineer—ideally early, to build a “golden list” of target accounts and to embed automation from day one. He also shares a strategy for convincing CEOs to fund AI initiatives: build quick, demonstrable pilots that deliver unexpected value. The episode closes with reflections on Clay’s growth trajectory, upcoming product releases, and the excitement of building GTM technology in the current AI era.

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