Fast Company revealed this week that Anything AI, a $100 million startup, is building AI employees with names, personas, and org chart positions. Emma handles onboarding. There are more of them. This is not a productivity tool. It is a new category of coworker, one that has no employment rights, no bad days, and, according to new academic research, no face to save.
Performance, Opacity, and the New Workplace
A 2026 arXiv paper, "The Fabricated Front" by van Nuenen, Sachdeva, and Chopra, argues that generative AI has made workplace performance fundamentally opaque. Managers cannot tell whether output is human or AI-assisted, and employees cannot tell whether their AI use is being monitored. Now insert a fully synthetic AI employee into that environment. The opacity doesn't just grow. It becomes structural. The AI employee is always performing, always available, never vulnerable, and never subject to the kind of unfiltered disclosure that Fast Company's Kristina Saffran argues is, ironically, a competitive advantage for human founders.
The Benchmarking Problem
A separate 2026 arXiv paper, CentaurBench by Wongchamcharoen and Nagaraj, finds that most LLM benchmarks measure automation, not augmentation. Most organizations deploying AI employees are making the same category error: evaluating output volume while missing questions about trust, accountability, and what happens when Emma gets the onboarding wrong. Slack's new vibe-coding channels, where teams code alongside AI agents in shared channels, are another node in this network. The workspace is not just being augmented. It is being repopulated. Whether the humans in that repopulated space will know who, or what, they are working with is the question nobody funding these startups seems to be asking. The Eugenia Kuyda model of software as something you raise and shape, rather than deploy as a fixed product, is the more honest framing, but it scales poorly for an org chart.