Are Tech Workers maxed out on their use of AI?

The NewYorkTimes.com reported that “Earlier this year, the message from tech companies to employees was clear: Use as much artificial intelligence in your work as possible.” The June 18, 2026 article entitled " Tech Workers Maxed Out Their A.I. Use. Now They’re Trying to Minimize It” (https://www.nytimes.com/2026/06/18/technology/ai-token-minimizing.html included these comments from Reporter Eli Tan:

 Employees called it “tokenmaxxing,” with a token referring to a unit of A.I. use roughly equal to a word fragment. Employees at Meta and Amazon even competed on leaderboards that tracked token use.

Then came the bills from companies, like Anthropic and OpenAI, that provide A.I. tools — and they were not cheap. Now the tokenmaxxing era appears to be over.

Meta told employees last week that it would soon limit A.I. use after seeing an “exponential increase” in costs. In May, Uber said it had blown through its projected A.I. spending for the year in just four months, and it has placed some monthly limits on A.I. coding tools. Walmart also set limits for different A.I. tools. And Amazon and Meta have taken down the tokenmaxxing leaderboards.

In other words, “tokenminning,” short for “token minimizing,” is now in.

The reversal, within just a few months, underlines how A.I. use remains in flux as people try to figure out how to best use the tools.

“The biggest problem is this is all changing so fast, people and companies don’t know what to do,” said Rob May, the chief executive of Neurometric, a start-up that helps companies better use A.I., and the author of “The Tokenminning Manifesto.”

“C.E.O.s who did not know how to measure the A.I. savviness of their employees thought, ‘Well, who’s using the most tokens?’” he said, adding that the philosophy ended up promoting volume over efficiency.

OpenAI and Anthropic offer subscriptions that cost $10 to $200 a month for use of their A.I. models; when subscribers hit their usage limit, they are cut off. But the bulk of the revenue comes from offering tools to companies like Meta, Shopify and Amazon, which pay not only subscription fees but also for the tokens used by their tens of thousands of workers. So the more tokens that are used, the more money the A.I. costs.

A simple task, like asking A.I. to summarize the transcript from a company meeting, may use a few hundred tokens. More complex requests, like writing code to build a new product or feature, can use tens of thousands.

Anyone surprised?