In the wave of AI artificial intelligence explosion, technology companies such as OpenAI, Anthropic or Meta are witnessing a new phenomenon when employees compete with each other based on the level of AI use.
The concept of "tokenmaxxing is maximizing the amount of tokens (AI's document processing unit)" is becoming a productivity symbol.
An engineer can process up to 210 billion tokens in just one week, while others spend more than 150,000 USD per month to operate AI systems like Claude or ChatGPT.
At some businesses, the amount of tokens consumed is even included in performance evaluations, turning AI into a new measure to replace traditional indicators.
Not only is it a supporting tool, AI is creating competitive pressure within the business. Employees try to use as much AI as possible to demonstrate productivity, even opening dozens of "agents" running in parallel day and night.
The development of automation programming tools has pushed this trend higher. AI systems can self-code, edit software and operate 24/7, creating millions to billions of tokens per week without constant human intervention.
This causes costs to skyrocket. Some programmers admit that spending on AI can be up to thousands of USD per day. Token, which was just a technical unit, has now become a "location measurer" in the working environment.
The token boom brings great benefits to AI providers. Revenue from these services increases sharply as demand increases.
However, many experts question the real effectiveness. Consuming a lot of tokens does not mean a better product. Some employees worry that colleagues are burning money just to show that they are catching up with the trend.
In fact, token rankings do not measure output quality, which is often the core factor of work. This raises suspicions that tokenmaxxing may just be a formal race.
In the context of AI spreading, not using new tools can become a career disadvantage. Many engineers consider operating AI systems as a strategy to assert their position.
However, this race also contains long-term risks due to high costs, psychological pressure and the risk of technology dependence.
Observers believe that the future will soon answer whether tokenmaxxing is a productivity advance or just a "bubble" in the AI era.
But one thing is for sure, to maintain this trend, the world will need many more data centers and computing resources.
