03/12/2026
There was a point in the RevOps Masterclass from Domestique where James Winter described using LLMs as an ex*****on layer for GTM work.
That framing resonated because it mirrors what I've been seeing firsthand.
LLMs are not just answering questions. They are accelerating how operators actually build things.
James talked about using tools like Claude Code to build landing pages, run data analysis, and interact with complex data environments without needing deep expertise in SQL or traditional data tooling.
He also described AI as a "really smart and really dumb employee." It moves fast, but it only becomes powerful when grounded in real context.
He used the frame of a "Context OS" to describe that grounding layer. Things like ICP, messaging, product details, competitors, and what customers are actually saying. It is a concept that has been gaining traction across the GTM space, and hearing it in that context made it click.
That part is critical.
When I run Claude Code inside VS Code and tie it into automation through n8n, the difference between generic output and useful output comes down to exactly that. Context.
When the model understands the systems, the data, and the objectives, it stops being a prompt tool and starts acting like an operational assistant helping build and move GTM infrastructure forward.
That shift is where a lot of the leverage is going to come from.
Not more dashboards. Better operators using AI to build and run the systems underneath them.
