Burn tokens to produce value, not points

Tokens are the cognitive fuel for an LLM but much like we wouldn't waste fuel for just anything, their use should be strictly controlled?

Conspicuous Compute

Take a look at the above image of a real leaderboard. They call it “tokenmaxxing.” Engineers and business users are competing to see who can burn the most AI tokens per month. Leaderboards are posted. Bragging rights claimed. Jensen Huang recently said he’d be “deeply alarmed” if a $500K engineer wasn’t burning through $250K in tokens a year.

Read that again. The CEO of the company selling the shovels wants you to dig more holes.

Conspicuous consumption, updated for the cloud era.

The old version: a Russian oligarch bathing in Cristal because he could. Stupid, but at least the champagne was real. The new version: Michael Lee at the top of the leaderboard burning through 5.8 billion tokens because … ok; we don’t know why he did it or what he produced.

There was a time, not long ago, when engineers cared about efficiency. Mainframe operators rationed compute like water in a desert. Every CPU cycle had a cost and a purpose. Then cloud computing arrived and the discipline evaporated. “Scale” became the excuse for waste. And now tokens have completed the transformation. They rebranded compute cycles, gave them a friendly name, and turned profligacy into a personality trait.

Cognitive Surrender’s Cousin

Recently, I wrote about cognitive surrender, the quiet trend of outsourcing judgment to AI. Tokenmaxxing is its financial cousin. One is about surrendering your brain; the other is about surrendering your budget. Both assume that more AI is always better.

Adam Smith saw this coming in 1776. In The Wealth of Nations, buried hundreds of pages past the famous bit about pin factories (as was the Invisible Hand), he warned that when a person’s work is reduced to a few simple operations, he “naturally loses the habit of such exertion, and generally becomes as stupid and ignorant as it is possible for a human creature to become.”

Smith was writing about the division of labor in early factories. Replace “few simple operations” with “prompting an agent to do your thinking” and the sentence doesn’t need updating. When you stop thinking because the machine thinks for you, you lose the muscle. Both lead to the same place: dependency without understanding.

In the movie Idiocracy, the population waters crops with a sports drink because an algorithm told them to. Crops die. Nobody can figure out why. The machines keep running. The humans keep not thinking. The movie set this hundreds of years in the future. They got the premise right but blew the timeline. We’re building that world right now, on a sprint, and celebrating the people who get us there fastest on a token leaderboard.

Nobody Left to Pay

Here’s what keeps getting ignored. The founders of the major AI labs enthusiastically predict the end of white-collar work. They describe a future where lawyers, analysts, consultants, and middle managers are replaced by agents.

Uh .. ok. Maybe. But if they’re correct, who pays for the tokens or the energy to create them?

If the white-collar workforce is gutted, who has the income to subscribe to the tools that gutted them? This is the dog catching the car. The entire business model depends on the continued existence of the people the technology claims to eliminate. Agents sell to agents, consuming tokens paid for by budgets that no longer have a revenue source.

There’s also the issue of what happens with the cranky displaced people which hasn’t ended well historically.

The Cerebellum Check

The cerebellum is the part of the brain that controls coordination. Balance. Knowing where your body is in space. The tokenmaxxing crowd is losing something similar: the coordination between spending and value, between capability and judgment, between what the machine can do and what it should do or, more accurately, how we should use it.

Before you celebrate your spot on the top ten list, ask one question: what did those tokens produce that you couldn’t have done with a tenth of them and five minutes of your own thinking?

If you can’t answer that, you might want to revisit not how many tokens you’re producing but why, what is being produced with them, and where is the value. If it’s not commensurate with the cost of the tokens rethink whether being on the leaderboard is a good idea.