“Collaboration” is often a polite word for inefficiency. In most organizations, it acts as a tax on the most productive people, dragging their pace down to the group average. Meetings and consensus-building aren’t “work”—they are the friction that happens when a system is poorly designed.
Software engineering solved this decades ago with a simple principle: Low Coupling, High Cohesion.
Build modules that do one thing perfectly (High Cohesion). Ensure they interact through clean, minimal interfaces (Low Coupling). This allows the system to scale without collapsing under its own weight.
For the first time, AI allows us to apply this engineering principle to human organizations.
In an AI-native firm, we don’t need “teams” in the traditional sense. We need a collection of highly specialized, decoupled agents. One for market analysis, one for content generation, one for lead qualification. They don’t need “alignment meetings.” They interact through APIs and data feeds—efficient, machine-to-machine, zero ego involved.
This shift is a total evaporation of the Coordination Tax. When you decouple the “how” (the execution handled by AI) from the “what” and “why” (the strategy handled by humans), the need for large, synchronized teams vanishes. You no longer need five people to agree on a direction before a single line of code is written or a single lead is generated.
The human role changes from being a player on the field to being the Architect of the API. You define the inputs, you audit the outputs, and you design the logic that connects them. You aren’t “collaborating” with the machine; you are directing a high-leverage system.
Complexity used to require more people. In the AI-native era, complexity requires better architecture.
The goal isn’t to make collaboration “better.” The goal is to make it unnecessary, so that what remains is pure, undistilled creativity. That is the only way to build at the speed of logic.