Startup CEOs who are \u201ctokenmaxxing\u201d are bragging that they are spending more money on AI compute than it would cost to hire human workers. Astronomical AI bills are now, in a certain corner of the tech world, a supposed marker of growth and success.\u00a0\u201cOur AI bill just hit $113k in a single month (we\u2019re a 4 person team). I\u2019ve never been more proud of an invoice in my life,\u201d Amos Bar-Joseph, the CEO of Swan AI, a coding agent startup, wrote in a viral LinkedIn post recently. Bar-Joseph goes on to explain that his startup is spending money on Claude usage bills rather than on salaries for human beings, and that the company is \u201cscaling with intelligence, not headcount.\u201d\u201cOur goal is $10M ARR [annual recurring revenue] with a sub-10 person org. We don\u2019t have SDRs [sales development representatives], and our paid marketing budget is zero,\u201d he wrote. \u201cBut we do spend a sh*t ton on tokens. That $113K bill? A part of it IS our go-to-market team. our engineering, support, legal.. you get the point.\u201dMuch has been written in the last few weeks about \u201ctokenmaxxing,\u201d a vanity metric at tech startups and tech giants in which the amount of money being spent on AI tools like Claude and ChatGPT is seen as a measure of productivity. The Information reported earlier this month on an internal Meta dashboard called \u201cClaudenomics,\u201d a leaderboard that tracks the number of AI tokens individual employees use. The general narrative has been that the more AI tokens an employee uses, the more productive they are and the more innovative they must be in using AI.\u00a0Stories abound of individual employees spending hundreds of thousands of dollars in AI compute by themselves, and this being something that other workers should aspire to. There has been at least a partial backlash to this, with Salesforce saying they have invented a metric called \u201cAgentic Work Units\u201d that attempts to quantify whether all this spend on AI tokens is translating into actual work.\u00a0Shifting so much money and attention to using AI tools is, of course, being done with the goal of replacing human workers. We have seen CEOs justify mass layoffs with the idea that improving AI efficiency will reduce the need for human workers, and Monday Verizon CEO Dan Schulman said he expects AI to lead to mass unemployment.\u00a0But while big companies are using AI to justify reducing worker headcount, startups are using AI to justify never hiring human workers in the first place.\u00a0\u201cThis is the part people miss about AI-native companies – the $113k is not a cost, it is your headcount budget allocated differently,\u201d Chen Avnery, a cofounder of Fundable AI, commented on Bar-Joseph\u2019s LinkedIn post. \u201cWe run a similar model processing loan documents that would normally require a team of 15. The math works when your AI spend generates 10x the output of equivalent human cost. The real unlock is compound scaling\u2014token spend grows linearly while output grows exponentially.\u201dMedvi, a GLP-1 telehealth startup that has two employees and seven contractors was built largely using AI, is apparently on track to bring in $1.8 billion in revenue this year, according to the New York Times (Medvi is facing regulatory scrutiny for its practices). The industry has become obsessed with the idea of a \u201cone-person, billion-dollar company,\u201d and various AI startups and venture capital firms are now trying to push founders to try to create \u201cautonomous\u201d companies that have few or no employees.\u00a0Andrew Pignanelli, the founder of the dubiously-named General Intelligence Company, gave a presentation last month in which he explained that many of the \u201cjobs\u201d at his company are just a series of AI agents, and that he now usually spends more money on AI compute than he does on human salaries.\u201cWe\u2019ve started spending more on tokens than on salaries depending on the day,\u201d he said. \u201cToday we spent $4 grand on [Claude] Opus tokens. Some days it\u2019ll be less. But this shows that we\u2019re starting to shift our human capital to intelligence.\u201dWhat\u2019s left unsaid by these tokenmaxxing entrepreneurs, however, is whether the spend on AI compute is actually worth it, whether the money would be better spent on human employees, what types of disasters could occur, and whether any of this is actually financially sustainable.\u00a0Companies like OpenAI and Anthropic are losing tons of cash on their products; even though artificial intelligence compute is expensive, it is underpriced for what it actually costs, and it\u2019s not clear how long investors in frontier AI companies are going to be willing to subsidize those losses. Meanwhile, we have reported endlessly on \u201cworkslop\u201d and the human cleanup that is often needed when AI-written code, AI-generated work, and customer-facing AI products go awry. There are also numerous horror stories of AI getting caught in a loop and burning thousands of dollars worth of tokens on what end up being completely useless tasks. Regardless, there\u2019s an entirely new class of entrepreneur who seems hell-bent on \u201chiring\u201d AI employees, not human ones.<\/p>\n","protected":false},"excerpt":{"rendered":"