Chinese Tech Workers Confront Automation Fears as Colleague Cloning Tool Goes Viral

A Spoof Striking a Nerve

Tech workers in China are facing instructions from their employers to train AI agents to replace them, prompting a wave of soul-searching among early adopters. The anxiety intensified after a GitHub project called Colleague Skill went viral on Chinese social media. The tool claims to allow users to distill their colleagues' skills and personality traits to replicate them with an AI agent. Although created as a spoof, it struck a deep nerve among tech workers whose bosses are actively encouraging them to document their workflows to automate processes using tools like OpenClaw or Claude Code.

Colleague Skill was created by Tianyi Zhou, an engineer at the Shanghai Artificial Intelligence Laboratory. To set up the tool, a user enters the name of a coworker and adds basic profile details. The tool then automatically imports chat history and files from popular workplace apps Lark and DingTalk, generating reusable manuals that describe the coworker's duties and unique quirks. Zhou told the Chinese outlet Southern Metropolis Daily that the project was started as a stunt, prompted by AI-related layoffs and the growing tendency of companies to ask employees to automate themselves.

The Push for Workplace Automation

Amber Li, a 27-year-old tech worker in Shanghai, tested Colleague Skill by recreating a former coworker. Within minutes, the tool generated a file detailing how that person did their job, capturing their punctuation habits and reactions. Li noted that she could use the resulting AI agent to debug code and reply instantly, though she described the experience as uncanny and uncomfortable.

Bosses in China have been pushing employees to experiment with agents since OpenClaw became a national craze. While AI agents can perform tasks like reading news, replying to emails, and booking reservations, workers note their business utility remains limited. Forcing employees to create detailed manuals of their day-to-day jobs helps bridge this gap. Hancheng Cao, an assistant professor at Emory University who studies AI and work, explains that this process helps firms gain rich data on employee know-how, workflows, and decision patterns to see what can be codified.

For employees, the process of creating these blueprints can feel deeply alienating. One anonymous software engineer trained an AI on their workflow and found the process felt reductive, flattening their work into modules and making them easier to replace. On social media platforms like Rednote, workers have turned to bleak humor, with one user joking that distilling coworkers first might help them survive layoffs a little longer.