Tokenmaxxing: When AI Becomes an Absurd Race

Discovery of a Confounding Practice

When I first came across the concept of tokenmaxxing, I thought it was a joke. The idea that users of conversational AI might consider completely exhausting their monthly credits as an achievement seemed absurd to me. Yet, this practice is gaining traction in the United States.

The principle is simple: some users strive to consume all their credits by asking the AI to rephrase the same sentence multiple times, engaging in endless conversations, or generating unnecessary text. On social media, tips are circulating on how to "maximize" their subscription by depleting their credits, and some take pride in it.

Then, I began to see serious discussions emerge, accompanied by screenshots. Users explained how to "maximize" their subscription by making the AI talk for hours. That’s when I realized this wasn’t a joke, but rather a symptom of a deeper problem.

The Reality of Tokens

To understand this trend, it is essential to know what a token is. It is a fragment of text used by language models to process data. This can be a word, part of a word, or even a punctuation mark. Every interaction with an AI consumes tokens, whether when sending a request or receiving a response.

This consumption has a real cost, whether financial, energy-related, or computational. Behind every AI response, there are servers, calculations, and electricity. This cost is justified when it produces something useful, but becomes absurd when it is an end in itself.

In my daily usage, I rarely see the message "you have reached your usage limit." And honestly, that reassures me. It means I use the tool when I need it, not to run it unnecessarily.

Organizational Pressure and Stress

My brother recently called me, visibly stressed. His manager had asked the entire team to prove in black and white how AI was increasing their productivity. This request reminded me of a time when one might have asked every employee to prove the usefulness of the Internet in their work.

This logic has taken hold in many organizations since the rise of generative AI: AI must be used, regardless of why or how. Tools are deployed, teams are asked to adopt them, and adoption is measured in consumed tokens, open sessions, and reports generated through AI.

The result is predictable: people use AI. Sometimes without a real need, sometimes just to show they are "good employees of the future." And some, pushed to the limit by this logic, end up engaging in tokenmaxxing—consuming for the sake of consuming, because that’s what they have been implicitly asked to do.

Thoughtful Consumption vs. Tokenmaxxing

As an entrepreneur, I actually pay for tools, subscriptions, and API calls. Before launching an automation, I systematically question how many tokens a task will consume, whether the gain justifies this cost, and if there is a simpler and less expensive alternative.

Sometimes, I test an automation, calculate its actual consumption, and decide not to deploy it. Not because it doesn’t work, but because a simple script or a well-established manual process can achieve the same result at a much lower cost. These decisions, while not spectacular, make the difference between intelligent use of AI and spending without return.

Token consumption should be a decision criterion, not a goal in itself.

The Importance of Discernment

Tokenmaxxing is the opposite of thoughtful AI usage. It often results from an organization that has failed to explain to its teams why they should use AI, only that they must do so.

Organizations need teams that consume better, who know when AI provides real value, and when it is the wrong tool. I take pride in using the least number of tokens possible, not out of stinginess, but out of common sense. Using AI intelligently means understanding how to use it, knowing when it adds real value, and maintaining a critical perspective.

This skill is not acquired by exhausting a subscription, but by using AI as one should use any tool: with discernment.