Model companies accumulate proprietary data and processes from enterprises through Agent implementation services. Previously, companies like OpenAI and Anthropic have similarly internalized client knowledge through enterprise customization and fine-tuning paths. The FDE strategy continues the capital cycle from service to model enhancement.

In terms of capital pathways, companies first generate cash flow through Token sales and consulting, then convert accumulated Skills into model capabilities. The motivation is to build a data flywheel and network effects, shifting resources from external implementation projects to internal model iterations.

Similar cases of AI Agent platforms penetrating various industries indicate that the current digital transformation of enterprises is transitioning from tool adoption to comprehensive Agent reconstruction. Software engineers who understand AI gain a buffer by participating in Skills development.

Essentially, this represents technological substitution and capital concentration: FDE accelerates the automation of knowledge work, with the mechanism being that corporate data feeds back into the model to form a closed loop, prompting human capital to concentrate on AI-related roles, while model companies achieve a structural shift in pricing power from services to platform subscriptions through Skills internalization.

ABAB News · Cognitive Law

Helping enterprises build Agents ultimately allows models to overcome corporate knowledge barriers.
Efficiency improvements first reduce costs, then assess whether business can keep up with expansion.
AI is sweeping across all industries; engineers who understand AI implementation will be the last to be replaced.