Using GenAI runs up tokens costs, and floods the world with content. But all too often that content — created by a giant but unreliable word prediction machine that is more regurgitative than innovative — is of little lasting value.

Maybe the biggest exception is coding, but even there, it’s not yet clear how many of the systems that have been created with the help of agentic coding will endure.

Moreover, especially in agentic coding, there are massive losses, up and down the food chain. The providers (Open AI, Anthropic, Cursor, etc) lose tons of money, and are scrambling to raise prices, Customers are balking at the new usage models.(In a new analysis, Gerben Wierda has argued that Anthropic and OpenAI “may actually pay $1000 for every $100 you pay them”. Data center intermediaries like CoreWeave are also losing money. It’s hard even to say how the chip companies are doing, once you factor out all the circular financing and shrinking cash flow. The one possible major productivity story (coding) also happens to be the one burning the most cash.

It could well be that once the providers (Open AI, Anthropic, Cursor, etc) attempt to charge enough money to cover their losses, the cost of AI could become more expensive than the humans it is replacing.