4.1 The Swing of Management: Digital Taylorism

In the previous chapter, like biologists dissecting a new species in a laboratory, we finally saw the internal structure of the "Silicon-based Employee": it is driven by probability rather than logic, has memory but no emotion, and has a heartbeat but never tires. Now, a trickier question lies before us: When you have such an army made of code, how do you become their general?

The answer might make many modern managers uneasy: Almost all the management knowledge you were proud of in the past needs to be thrown into the dustbin of history.

For a century, the mainstream narrative of management has been a history of constant "humanization." We first bid farewell to Frederick Taylor's cold stopwatch, who viewed workers as machine parts and pursued extreme efficiency and standards[^1]. Then, Elton Mayo accidentally discovered in the lighting experiment at the Hawthorne Works that "attention" was more magical than "money," opening the Pandora's box of "Social Man"[^2]. Consequently, from Maslow's hierarchy of needs to Herzberg's two-factor theory, managers transformed one after another, learning to become half psychologists and half career coaches. They learned to listen, to empathize, and how to build a sense of belonging and mission. The entire management toolbox was filled with precision instruments targeting complex human emotions and psychological needs.

But when your management object changes from flesh-and-blood "Carbon-based Life" to absolutely rational "Silicon-based Code," all this instantly fails. This is tantamount to sending a team of the world's top psychologists to repair the operating system of a supercomputer—their exquisite tools regarding empathy, motivation, and psychological intervention will completely malfunction in front of cold code. Your toolbox is useless. The AI employee, this brand new species, completely wipes humanity out of the management equation. It doesn't need psychological massage because it has no mood swings; it doesn't need career planning because it has no personal ambition; and it certainly doesn't need team building or corporate culture to maintain loyalty because its tendency to "resign" is zero. Trying to use Maslow's theory to motivate a large language model is like trying to feed dry grass to an F1 racing car; this is a profound "Paradigm Mismatch." We are facing the most thorough rupture in the history of management, where all theories revolving around "people" have run aground.

This upheaval has not left a vacuum in management but instead triggered a violent "pendulum swing." We are not creating a brand new management philosophy, but rediscovering Taylor's "Scientific Management" in the digital world with unprecedented scale and precision. This is not a simple historical regression, but the rebirth and sublimation of "Taylorism" driven by algorithms, which we call—Digital Taylorism.

The soul of Taylor's thought lies in breaking down all complex labor into "Standard Operating Procedures" (SOP) and firmly believing in the existence of "The One Best Way." A century ago, SOPs were disciplines written on paper that required workers to recite and abide by, and the execution effect was full of uncertainty. In the AI era, SOPs have undergone a qualitative change: they are no longer instruction manuals guiding employees; SOP itself is code, is that absolutely obedient employee. In multi-agent frameworks like MetaGPT, complex software development tasks are forcibly broken down into a series of solidified Lego blocks such as requirement analysis, architecture design, coding, and testing. Each Agent can only complete its standard actions strictly on the prescribed interface[^3]. This is exactly the perfect assembly line Taylor dreamed of. It uses the rigid constraints of code to replace the earnest advice to human nature, thereby greatly enhancing the certainty of the system and effectively inhibiting the "hallucination" and "off-topic" behaviors of large language models caused by excessive freedom.

"SOP as Code" is the core of Digital Taylorism, and the fuse igniting this revolution is "Natural Language Programming." It completely dismantles the wall between process automation and business experts, achieving an amazing democratization of the power of "programming." It's like you don't need to learn any mechanical engineering knowledge to write a recipe for a kitchen robot.

Taking "Agent Skills" launched by Anthropic as an example, a sales director who knows the business well but has no programming background can now "teach" AI a new skill by writing a simple Markdown file[^4]. He only needs to describe the goal of the skill in plain language ("Go to Salesforce to check the recent order history of Customer A"), provide a few clear examples, and define the tools to be called (such as internal company APIs). Within minutes, a software function that originally took days to develop is "compiled." This document written in natural language is a "magic recipe" that can be read and executed by AI.

This marks a historic power transfer: the power to define and optimize "The One Best Way" is being released on a large scale from the hands of a few software engineers to every domain expert who truly understands the business. Management, in the AI era, is returning to its engineering essence unprecedentedly, and managers are becoming the "Architects" of a new species.

[^1]: Scientific Management Theory. Proposed by Frederick Taylor in the early 20th century, it decomposes workflows into standardized tasks through "time-motion studies" to maximize efficiency, laying the engineering foundation for modern management. Reference HEFLO, "From Taylorism to ESG: Tracing the Evolution of Management Practices", 2026. Article Link [^2]: Human Relations School. Originating from the Hawthorne Experiments in the 1920s, this experiment accidentally discovered that employee productivity is not only affected by physical conditions but also hugely influenced by social and psychological factors (such as the sense of being paid attention to), shifting the focus of management from "things" to "people." Reference The ExP Group, "A timeline of management theories", 2026. Article Link [^3]: Multi-Agent Collaboration Framework MetaGPT. This framework highly structures complex software development processes by setting strict SOPs and document formats for AI agents of different roles (such as product managers, engineers). It is a typical implementation of "Digital Taylorism" in the field of code generation. Reference SmythOS, "MetaGPT Vs ChatDev: In-Depth Comparison And Analysis", 2026. Article Link [^4]: Claude Agent Skills. A feature launched by Anthropic that allows users to define tools and capabilities that AI agents can call using natural language and simple Markdown formats, greatly lowering the threshold for non-technical personnel to create and orchestrate AI workflows. Reference Anthropic, "Skill authoring best practices - Claude API Docs", 2026. Official Documentation