陈天桥发文：当管理退出 认知升起，KPI崩塌了！

Core Insights - The future of management will be fundamentally based on intelligence rather than biology, marking a shift from human-led to AI-augmented enterprises [1][2] - Traditional management systems are seen as corrective measures for human cognitive limitations, which will collapse as AI agents take over execution roles [2][4] - The emergence of AI-native enterprises will redefine organizational structures and operational paradigms, focusing on cognitive evolution rather than resource management [4][5] Summary by Sections Management Paradigm Shift - Management will transition from being human-centered to AI-native, where AI expands human capabilities rather than being managed by humans [1][2] - The introduction of AI agents will disrupt the biological foundations of traditional management, necessitating a complete rethinking of organizational genetics [1][2] Cognitive Anatomy Comparison - A comparison between human employees and AI agents highlights three key differences: continuous memory (AI's eternal memory vs. human's fragile memory), holistic cognition (AI's full alignment vs. human's hierarchical filtering), and endogenous evolution (AI's self-evolving capabilities vs. human motivation-driven evolution) [3][4] Collapse of Traditional Systems - Traditional KPIs are becoming obsolete as AI agents can navigate complex problem spaces without rigid constraints, unlike human-centric systems that were designed to mitigate cognitive shortcomings [4] - The existing supervisory frameworks are shifting from error correction to recalibrating goals, as AI agents understand and execute tasks without the need for constant oversight [4][5] Definition of AI-native Enterprises - AI-native enterprises will require a new operational framework focused on cognitive evolution, characterized by five aspects: architecture as intelligence, growth as compounding, memory as evolution, execution as training, and humans as meaning-makers [5][6] - The demand for talent is shifting towards mid-career professionals with specialized knowledge, as AI reduces the need for generalist analysts [5][6]