All episodes June 30, 2026

Rise of GTM Engineers, the Age of Hyper-Personalization, and the New AI Pricing Loop

Doom and Quinn discuss trends in AI and go-to-market, including Frontier model updates (notably prompt retention changing to 30 days), massive capital raises (Google, SpaceX, and anticipated AI funding), tightening budgets, and the push toward agentic security. They focus on the rise of GTM engineers as roles collapse into technical, full-cycle sellers, debating where this works (e.g., Clay) and where it doesn’t. They explore enterprise knowledge graphs that ingest email, Slack, and meeting notes, noting potential “internal slop,” and share a workflow that turns a long proposal into an interactive HTML site with revenue sliders, plus hurdles like hosting and deployment. They review a McKinsey study of 4,000 buyers showing winners outperform laggards via hyper-personalization, AI, and ABM governance. They also cover a framework contrasting frontier vs saturated tasks and public vs private data, Harvey/Fireworks cost routing, and Satya Nadella’s view that pricing cycles between seats, consumption, and outcomes, ending with commentary on Jeff Bezos’s new engineering-focused AI startup.

00:00 Cold Open Banter

00:59 AI Headlines Roundup

04:03 GTM Engineer Debate

07:01 Sales Automation Matrix

09:04 Knowledge Graph Slop

10:13 Interactive Proposal Demo

15:10 Reticular Activator Story

17:42 McKinsey ABM Shift

24:10 Private Data Moat Framework

28:10 Harvey Fireworks Margins

31:20 Enterprise Adoption Limits

33:56 Pricing Models Go Circular