Meta created an internal AI token leaderboard (tokenmaxxing)
Source: Gregor Ojstersek, Engineering Leadership; follow-up Sify · 2026-04-09
At Meta, they’ve gone the next step. They created an internal leaderboard ranking employees based on how many AI tokens they use.
The problem with such a leaderboard is that if token usage becomes the metric, then token usage becomes the goal. And that’s where things can go sideways quickly.
This is the name of the leaderboard at Meta, and it tracks AI token usage of over 85k employees. Interestingly, this has been a bottom-up initiative, built by engineers and shared on the company’s intranet.
Some unofficial data I have seen based on my research:
There are also different badges, from bronze, silver, gold, platinum, to emerald, awarded to people, and the top 250 people in the leaderboard are considered “power users” and can get additional badges like “Session Immortal” and “Token Legend”.
So, it’s like a game of who is using the most tokens. But the actual question is:
Is the use of tokens actually going in the right direction? Solving actual business problems?
The trend seems to be called “tokenmaxxing”, where token consumption is treated as a benchmark for productivity and a competitive metric to determine if an employee is “AI-native”.
Stated that he would be “very concerned” if an engineer earning $500,000 annually spent less than $250,000 on AI tokens each year.
Delivered a keynote to the company’s engineering team, where he highlighted a particular engineer who had used over $7,000 worth of AI tokens within just two weeks in January.
Rather than criticizing the high spending, Ghodsi used it as a positive example. And mentioned: “We actually had the whole engineering team applaud him and recognize his efforts. My goal is to encourage everyone to start using these tools.”
Said at a tech conference in February that a top engineer who spent an amount equivalent to their salary on AI tokens saw a productivity increase of up to 10 times. And mentioned: “It’s a no-brainer, keep doing it, there is no upper limit.”
Said on a podcast: “The name of the game is tokens. How can you maximize your token throughput and not be in the loop”.
Using token consumption as a benchmark for productivity.
I am also hearing the following: Some employees at Meta, in order to climb the leaderboard, they let AI agents run continuously for hours to perform research tasks, maximizing token consumption.
There seems to be a lot of other companies doing something similar as well, it’s not just Meta.
My company has been doing something like this as well, and it’s as stupid and easily gamed as you would expect. Right up there with measuring lines of code or using story points to gauge productivity.
The best way to rack up tokens seems to be keeping a chat context going for a long time, telling it to read tons of code (multiple repos for extra points), and pasting as much code or text into the chat as you can.
It’s official in the company I work for, but in our case, if you don’t reach an AI usage threshold each week, you are fired.
And there have been more similar cases like these. Some other engineers I talked to have also mentioned that they either are judged based on token usage in their company or they know someone who is.
Based on the company names, the majority of such companies are based in Silicon Valley. I believe the trend of “tokenmaxxing” is less common in companies outside of that bubble.
Is judging people based on token consumption the right way to go?
Lines of inquiry this paper opens 2
Research framings built by reading the notes related to this paper — the questions it feeds into.
Does AI-assisted work increase total productivity or just shift time?