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Someone gave every rep a Claude license. Every team built its own ChatGPT project. Now the same question gets two different answers depending on who you ask. One customer had a rep pitch a product line that did not exist because ChatGPT made up SKUs the company had never sold. The model was not the problem. The agent was not the problem. The architecture underneath was.
Alex Bilmes built Endgame to fix that architecture. He has raised over $47M for Endgame, with customers including Braze, Scale AI, BetterUp, and Monte Carlo. Monte Carlo reached 80% AI adoption across its GTM team running on the platform.
In GTM 46, Alex breaks down why revenue is the GTM function furthest behind on AI despite being the function that makes the money, why connecting Claude directly to a stack of MCP servers produces inconsistent answers at scale, and the new function that controls how every rep sells. He explains why agentic hellscape is the default state of most enterprises right now, why revenue per employee is the metric every CRO is laddering to, and why the best leaders are the ones spending nights and weekends building with AI on their own accounts.
This is not a conversation about better AI tools. It is a conversation about the architecture that determines whether every tool you bought produces leverage or sprawl.
Read the full write-up: https://www.gtmvault.co/p/gtm-46-context-is-gtm-infrastructure
