Moats Built for Humans
Software moats—workflow lock-in, interface training, data silos—were built to stop humans. AI agents bypass all of it. The $300B wipeout was the market catching up to a structural shift.
EnterpriseAI
13 posts
AI Labs: The Great Filtration
SSI, Thinking Machines, World Labs, Humans&—each represents a different bet on AI's future. But ambition isn't the variable that matters. Scarcity is. The Great Filtration will separate those who control something defensible from those who don't.
The Quiet Revolution: Why Your Organization Is About to Become Something Entirely New
The AI advantage won't come from smarter tools, but from organizations that treat intelligence as infrastructure. Scattered deployments compound into complexity and fatigue, not competitive advantage. The firms that thrive will build systems where intelligence accumulates.
The Hardest AI Question Isn't 'What' or 'How'—It's 'Where'
Diffused AI strategies yield marginal, replicable gains. Deep concentration in one domain—chosen via three filters: infrastructure needs, workflow centrality, and measurability speed—creates competitive moats. Commitment to execution matters more than perfect selection.
The Sovereignty Transition: Reclaiming Control in a High-Velocity AI Environment
AI sovereignty isn’t about replacing vendors, it’s about controlling intent. In a world where models evolve every six months, enterprises must own the logic that governs decisions while treating execution as swappable. Control the architecture, not the tools.