AI may be taking over the workplace, but Meta employees apparently won't need to prove how enthusiastically they're using it anymore. Meta has updated its performance review guidance so employees will no longer be evaluated based on how much they use AI tools, moving away from AI-usage language and back to something simpler: the actual impact of their work.
It sounds obvious, but the distinction matters. Last year Meta told workers that "AI-driven impact" would factor into evaluations, encouraging employees to incorporate chatbots into their jobs. Workers could receive labels like "AI Native," "AI First," or "AI Enabled" based on adoption. The result, according to some employees, was a workplace where using AI could become a goal in itself.
Some employees began prompting AI tools more frequently just to boost internal usage numbers, watching how many tokens they consumed. Things got competitive enough that one employee created an internal leaderboard ranking colleagues by AI usage, complete with titles like "Token Legend." It was eventually removed after details became public.
Meta is now clarifying expectations. Engineers were told AI adoption dashboards and token counts won't be used to measure their impact. The updated language says employee outcomes "can be supported by AI or other means" - using AI is still encouraged, but it isn't the point.
Don't mistake the change for Meta losing interest in AI. Employees have been testing an experimental agent called Hatch that can take actions on a computer, browse the web, and interact with applications. It could eventually get a public release. When a company reaches the point where employees compete to become "Token Legends," judging the work rather than the token counter probably isn't the worst reset. The lesson for any company pushing AI adoption: tools are means, not ends.