Core Viewpoint - The rise of AI agents signifies the "twilight" of traditional management practices, necessitating a fundamental shift in organizational structure from a "human-centered" to an "AI-native" paradigm [1][5][25] Group 1: AI Agents as New Entities - AI agents possess three core advantages: continuity of memory (everlasting memory vs. transient), holistic cognition (full alignment vs. hierarchical filtering), and endogenous evolution (reward model-driven vs. dopamine-driven) [2][11][13] - The introduction of AI agents will disrupt existing management systems, as they operate under fundamentally different physical laws compared to human employees [2][10] Group 2: Redefining KPIs and Supervision - Traditional KPI systems will collapse as they were designed to guide human behavior, which is not applicable to AI agents that can continuously lock onto target functions [3][14] - Supervision mechanisms will also need to be redefined, shifting from monitoring execution to recalibrating goals, as AI agents understand and execute tasks inherently [3][16] Group 3: Characteristics of AI-native Enterprises - AI-native enterprises will have five defining characteristics: 1. Architecture as Intelligence: Organizational design will focus on maximizing data throughput and intelligent emergence rather than risk control [4][17] 2. Growth as Compounding: Valuation will depend on the speed of cognitive compounding rather than headcount [4][18] 3. Memory as Evolution: Organizations will require a writable and evolvable long-term memory hub to facilitate decision-making [4][19] 4. Execution as Training: All departments will function as model training units, where every interaction contributes to the internal world model [4][20] 5. Human as Meaning: Humans will transition from being mere resources to roles that define intent and ethical direction [4][21] Group 4: The Future of Management - Management will not disappear but will be fundamentally restructured on the basis of intelligence rather than biological limitations [5][25] - The infrastructure supporting organizations must evolve to accommodate this new form of intelligence, moving away from outdated systems that cannot support the fluidity of AI [23][24]

Core Viewpoint - The article discusses the transformative impact of artificial intelligence (AI) on management practices, suggesting a shift from human-led management to AI-driven organizational structures [3][4]. Group 1: New Cognitive Paradigm - The emergence of AI agents with advanced cognitive abilities will disrupt the traditional management framework based on human biological limitations [4][5]. - Companies need to transition from a "human-centric" management paradigm to an "AI-native" cognitive paradigm, fundamentally reshaping their organizational DNA [5][6]. Group 2: Collapse of Traditional Systems - Traditional management systems, which were designed to compensate for human cognitive limitations, are becoming obsolete as AI agents take over execution roles [5][7]. - Key Performance Indicators (KPIs) are becoming less relevant, as AI agents can navigate complex problem spaces without rigid constraints [7][8]. - The supervisory mechanisms that were once necessary for human oversight are now redundant, as AI agents can understand and execute tasks autonomously [7][8]. Group 3: Definition of AI-native Enterprises - AI-native enterprises require a new operational framework focused on cognitive evolution rather than resource management [7]. - The five aspects defining an AI-native enterprise include: 1. Architecture as intelligence, shifting focus from risk management to maximizing data throughput and intelligent emergence [7]. 2. Growth as compounding, where valuation is based on the speed of cognitive structure compounding rather than headcount [7]. 3. Memory as evolution, necessitating a long-term memory hub that continuously updates organizational knowledge [7]. 4. Execution as training, where all departments function as model training units, updating the internal world model with each interaction [7]. 5. Humans as meaning-makers, transitioning from being mere resources to becoming curators of intent and cognitive architects [7]. Group 4: Industry Trends - The article highlights a broader trend where AI is reshaping organizational structures, reducing the demand for generalist analysts while increasing the need for mid-career professionals with specialized knowledge [8]. - Companies are adopting a "box model" structure, where the number of senior and junior employees is becoming more balanced, emphasizing the role of experienced professionals over entry-level analysts [8].

Core Insights - The future of enterprises will shift from being human-led to being expanded by intelligence, as proposed by Chen Tianqiao, founder of Shengda Group and Tianqiao Brain Science Research Institute [1][2] - Management science will not disappear but will be fundamentally based on intelligence rather than biological limitations [1][2] Group 1: Transformation of Management Paradigms - The emergence of AI agents with advanced cognitive abilities will disrupt the traditional management paradigm, necessitating a shift from a human-centered approach to an AI-native cognitive framework [2][3] - Traditional management systems were designed to compensate for human cognitive limitations, but as AI takes over execution, the foundation of these systems will collapse [2][3] Group 2: Cognitive Anatomy and AI Advantages - Chen Tianqiao highlights three key differences between human employees and AI agents: continuity of memory (eternal vs. ephemeral), holistic cognition (full alignment vs. hierarchical filtering), and endogenous evolution (reward-driven vs. dopamine-driven) [3] - AI agents are not merely stronger employees but represent a new species operating under different physical laws [3] Group 3: Collapse of Traditional Structures - The introduction of AI agents leads to the collapse of traditional KPIs, which were designed for human navigation but limit AI's potential to explore optimal paths [4] - Traditional oversight mechanisms are becoming redundant as AI agents execute tasks based on understanding rather than supervision [4] Group 4: Definition of AI-Native Enterprises - AI-native enterprises require a new operating system focused on cognitive evolution rather than resource planning, characterized by five aspects: architecture as intelligence, growth as compounding, memory as evolution, execution as training, and humans as meaning-makers [4][5] - The article emphasizes the need for organizations to evolve their structures to maximize data throughput and intelligent emergence rather than merely managing risks [5] Group 5: Industry Trends and Implications - The impact of AI on organizational structures is gaining global attention, with consulting firms noting a reduced demand for generalist analysts and a shift towards mid-career professionals with specialized knowledge [5] - Companies are moving towards a "box model" structure, where the number of senior and junior employees is becoming more balanced, relying on experienced professionals rather than a large number of junior analysts [5]