陈天桥发文：AI时代，管理退场认知上位，KPI体系要塌了！

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The infrastructure supporting organizations must evolve to accommodate this new form of intelligence, moving away from outdated systems that cannot support the fluidity of AI [23][24]