From AI uncertainty to GTM advantage. And why most GTM teams solve the wrong problem.
The teams winning with AI are not the ones running the most experiments. They are the ones who defined the problem worth solving first.
View on LinkedIn →Insights
Short reads on what's shifting. Longer reads on what it means.
The teams winning with AI are not the ones running the most experiments. They are the ones who defined the problem worth solving first.
View on LinkedIn →Governance is not the enemy of speed. The right operating model makes both possible at the same time.
View on LinkedIn →The plan was not the problem. The operating model built to execute it was. Most organizations are still confusing strategy with a slide deck.
View on LinkedIn →Not the demos, not the pilots. The deployments that moved the number. The pattern is not what most organizations are still chasing.
View on LinkedIn →The organizations getting real returns from AI are connecting it directly to pipeline, conversion, and retention. Everything else is overhead.
View on LinkedIn →The gap between the plan and the operating model built to execute it is where most growth strategies die. It is not a strategy problem.
View on LinkedIn →The organizations winning with AI are not the ones with the most tools. They are the ones that built the data, process, and cross-functional systems before they scaled. A framework for thinking about AI as an operating decision first.
GTM StrategyVolume-based GTM models were built for a different era. As consumption, usage, and outcome-based pricing become the norm, every assumption about demand generation, pipeline, and customer success needs to be rebuilt.
GTM ExecutionEvery leadership team has a strategy. Very few have the operating model that makes it executable. The difference between organizations that hit their number and those that miss it is almost never the plan.