A new term is spreading among tech workers for people who pass AI-generated work to colleagues without reviewing or adding anything themselves. “Meat proxy” refers to a person who effectively acts as a go-between for an AI chatbot and another human. Instead of checking, editing or understanding what an AI system produces, the person simply forwards the output.
The term was popularized by German software engineer Niklas Gruhn in an August 3 blog post after he noticed people sharing AI-generated responses in Slack channels and group chats, according to Business Insider. The idea quickly gained attention among tech workers. Gruhn’s Hacker News post drew more than 700 comments, while the term spread across X and was picked up by other technology commentators.
The criticism is less about using AI itself than about what happens when employees remove themselves from the process entirely.
When AI output becomes someone else’s problem
The “meat proxy” label fits into a growing backlash against AI-generated workplace content that has not been reviewed by the person who produced it. That can mean sending an AI-written message without checking its accuracy, submitting AI-generated code without understanding how it works or forwarding an AI response that does not actually address the recipient’s question.
Other tech workers have offered similar labels, including “human ChatGPT wrapper,” as they debate whether employees are adding any value when they simply relay what a chatbot produces.
The concern also connects to the larger frustration over AI “slop,” a term increasingly used for low-quality, mass-produced AI content across the internet and in professional settings.
The human still matters
Not everyone sees the behavior as inherently problematic. Some developers have embraced the concept as part of a workflow in which one person handles communication with AI while another handles the reverse process.
But the criticism highlights a basic problem with workplace AI: generating an answer is not necessarily the same as doing the work. As AI tools become easier to use, employees who can evaluate, refine and apply their output may have a clearer role than those who simply pass it along.
