Looking back on this series, we have journeyed from the rigid organizations of the industrial age, through the individual anxieties of the information age, to the drift of purpose under the lens of capital—all in search of the ultimate meaning of “efficiency.”

Today, we stand at a historic inflection point defined by large models and generative AI. This is not merely a technological upgrade, but a paradigm shift touching the very foundations of civilization, compelling us to re-examine the nature of value, organization, and even humanity itself.

Previously, our discussions of efficiency and goals were based on a core assumption: human intelligence is a scarce and critical resource. Therefore, the primary task of an organization was to optimally allocate this scarcity. However, the emergence of large models is profoundly challenging this assumption.

In basic cognitive tasks, large models are creating a potential surplus of “intelligence.” This is not just an extension of physical labor or computing power, but a “universal interface for semantic understanding and generation”—like an amplifier for consciousness. It drastically reduces the cost of generating high-quality content, writing code, and performing strategic analysis, thereby shifting the nature of scarcity in value creation. The true scarcity is no longer execution, but “the ability to ask the right questions, exercise critical judgment, and imbue work with deeper meaning.”

This means that if an organization’s goal remains merely “efficiently completing assigned tasks,” it will lose its value foundation. It must pivot towards defining the fundamentally new, worthwhile problems that powerful AI should be deployed to solve.

This revolution in productivity will also drive a profound evolution in organizational forms. Coase’s theory of transaction costs posits that firms exist to reduce market transaction costs. Large models and collaborative technologies empower individuals, significantly lowering the costs of finding partners and managing projects, thereby undermining the traditional role of the company as the core economic unit.

The future landscape may see the rise of the “one-person economy”: highly specialized individuals leverage AI to handle the vast majority of execution work, focusing their energy on innovation and strategic connections. For complex tasks, these individuals could temporarily assemble into decentralized autonomous organizations (DAOs) via smart contracts. The core function of an organization shifts from “management and control” to “attraction and coordination,” and its goal transforms from a command into a foundational protocol for building consensus.

Alongside changes in organizational form, the criteria by which users judge value will also evolve. In an era of extreme abundance, the measure of value leaps from “does the function meet the need?” to “does the experience resonate and provide meaning?” Large models enable not only hyper-personalization but also make “co-creative” relationships possible. Experiences in education, healthcare, and entertainment could be dynamically generated based on individual feedback, making the user a co-designer of their own experience.

Consequently, a company’s goal must shift from “capturing user mindshare” to “co-evolving with the user.” Value is no longer a static product but an emergent outcome of continuous, deep interaction. An organization’s goal must become a dynamic compass, not a fixed destination.

In this context, the role of the leader must undergo a fundamental transformation. Leaders need to move from being “commanders” to “system architects” and “guardians of meaning.” Their primary task is to identify and protect non-optimizable human core values—such as privacy, fairness, compassion, and beauty—in the face of the seductive allure of efficiency, and to set these as the ethical boundaries for AI action.

Simultaneously, they must build the fields that foster innovation—not rigid processes, but the nurturing of rules, incentive mechanisms, and a cultural soil that allows for non-linear exploration and intuition-driven trial and error.

Ultimately, large model technology pushes efficiency to unprecedented heights, placing us at a crossroads of civilization. One path is “accelerated cycling,” descending into spiritual involution amidst material abundance driven by efficiency. The other path is a “value leap,” leveraging the productivity explosion to direct collective intelligence toward the grand challenges of human civilization: conquering disease, exploring the cosmos, understanding consciousness, creating art, and dissolving inequality.

Large models themselves hold no predetermined answers; they act like a mirror, reflecting the collective will of our civilization. They pose an ultimate question to society: When technology is no longer the primary constraint, what is the goal we collectively pursue? This technological revolution ultimately tests not just corporate strategy, but humanity’s capacity for imagination and choice regarding its own future.

Efficiency is no longer just a means; it becomes a magnifying glass that tests the depth of our goals and the direction of our values. Only by clarifying the “why” can the “how to be efficient” truly serve humanity’s long-term vision.