Chinese Tech Companies Are Ordering Employees to Build AI Copies of Themselves

Chinese technology companies have crossed a line that was previously discussed only in theory: engineers are being directly asked to train AI agents that can do their jobs. This is no longer an abstract threat of automation. It is a direct corporate assignment that puts the worker in a fundamentally new position.

In early April 2026, a project called Colleague Skill appeared on GitHub. Its authors described the tool simply: it lets you "distill" the skills and personality traits of colleagues to create a digital twin of them. In practice, that means training an AI to reproduce a specific person's professional behavior: their decision-making style, communication patterns and working heuristics. The project immediately drew attention in the Chinese tech community and set off a wave of public discussion that MIT Technology Review called "painful soul-searching."

Notably, this wave did not come from skeptics of the technology but from its strongest supporters. Chinese developers and engineers have generally been among the most AI-friendly workers: they actively experimented with new tools, were the first to bring them into their workflows, and publicly promoted what the systems can do. Now those same people have been asked to become the architects of their own replacement. It is this gap between belief and reality that struck such a nerve.

The situation exposes a fundamental contradiction in how companies present AI transformation. The narrative that "AI is a tool that makes you more efficient" sharply diverges from the reality of a corporate assignment that says "train an agent that will work in your place." The difference is not cosmetic: it changes the employee's very position. From a user of the technology, a person becomes its object, a source of data from which value is extracted, rather than a partner in the rollout.

Similar signals are coming from other sectors in Asia. Companies in software development, content production and technical support are increasingly testing arrangements in which an employee's key task at a certain stage is to "offload" their knowledge into a system. After that, an agent takes over running the processes. This does not always mean immediate layoffs: some employers position the approach as scaling up capabilities. But employees understand that their role in this model is finite.

Colleague Skill made the invisible visible. Previously, similar processes ran informally: companies analyzed work data, logged employees' actions and studied decision-making patterns. Now it is an open, documented request: describe your decisions, systematize your heuristics, help build your digital copy. This transparency is, paradoxically, more unsettling than covert data collection, because it removes the possibility of keeping up illusions.

There is also an ethical question that is barely discussed in public so far. Does an employer have the right not only to demand the results of work, but also to require an employee to systematically hand over the very ability to produce them? Labor law in most countries has no answer to this question. It is a fundamentally new form of alienation: not of the product of labor, but of cognitive capital as such.

For the labor market in the tech sector, this changes the basic value equation. Traditionally, a specialist's tacit knowledge (accumulated experience, intuition, an understanding of context and nuance) was considered hard to reproduce. That is what made a skilled employee irreplaceable. If this knowledge can now be systematically extracted and scaled through an agent, the protective barrier disappears.

The reaction of the Chinese tech community showed that the line where enthusiasm for AI turns into existential anxiety is much thinner than assumed. It is an important signal for the whole industry: the pace of automation has reached a point where abstract narratives about "reskilling" and "new roles" no longer work as reassurance. The next question is not "will AI replace people," but "who is responsible for the process of replacement."