Success creates a "reinforcement learning" loop, codifying a firm's methods. When a paradigm shifts, like the move to AI, this reinforced playbook becomes a liability. The more successful a firm was in the prior era, the harder it is for them to adapt to new, foundational business assumptions.

Educational institutions that still prioritize memorization and writing from scratch are failing to prepare students for the AI era. These skills have been commoditized by technology. Graduates are entering a job market that values synthesis, critical application, and adaptability, leaving them unprepared and potentially unemployable.

The unique danger of an AI-driven transformation is its unprecedented speed. Unlike past revolutions that unfolded over centuries, AI could reshape society in decades or less, overwhelming our institutions' ability to adapt, similar to how it took 50 years to get the Paris Climate Agreement.

The education system effectively produces what it was designed for: compliant workers for a rote-job economy. The problem isn't failure, but a failure to adapt its goals from the industrial era to the innovation era, where creativity and initiative are paramount.

In the AI era, the pace of change is so fast that by the time academic studies on "what works" are published, the underlying technology is already outdated. Leaders must therefore rely on conviction and rapid experimentation rather than waiting for validated evidence to act.

Today's higher education was designed to train a literate workforce for industrial corporations. The AI revolution represents a societal shift of similar magnitude, requiring a complete redesign of how we train young people for a new world of work and problem-solving.

Large institutions, even those designed to foster innovation, are fundamentally conservative. Their investments in real estate, careers, and the status quo make them inherently resistant to the revolutionary change that defines major breakthroughs.

The disruption from AI is not incremental but a fundamental environmental shift, like water turning to gas. No matter how good you are at "swimming" (your current skills), those skills become useless when the environment's physics change, requiring entirely new modes of operation.

Past technological shifts occurred over decades, allowing labor markets to gradually adjust. AI's disruption is happening over years, a speed that historical models can't account for. This compressed timeline means new jobs and retraining won't happen fast enough, demanding immediate policy interventions like expanded capital ownership.