Token Spend Is the New Cloud Bill

Every few years, business gets a new line item that makes the finance department nervous. First it was software licenses. Then it was cloud hosting. Now it's tokens, the units AI companies charge for every word a model reads and writes.

Lately, you'll hear people predict an AI "backlash" as companies notice how fast those bills add up. I don't buy it. Companies trim cloud, SaaS, and headcount every budget cycle, and nobody calls that a revolt. It's a correction. The people getting real returns keep spending. Everyone else cuts back quietly.

What real returns look like

In September 2026, Nous Research published a striking example. They pointed their Hermes agent at a million lines of messy Python code and let it clean house. Over about 19 active hours, it dispatched 1,393 smaller AI agents, with up to 218 running at once. When it was done, the code was 34.4% smaller.

The model bill came to about $19,300 for the main run, roughly $25,000 with follow-up sessions. Nous estimated the same work by hand would have cost $150,000 to $1.8 million, taking a small team anywhere from two months to two years.

That's the kind of math that keeps companies spending.

The fine print matters

Those numbers leave out human review time, and that part wasn't optional. People reading the changes caught problems the automated tests missed, including deleted names that outside plugins depended on and altered error handling in dozens of places. The AI did the heavy lifting. Humans still had to check the work.

That lines up with another study out of the University of Stuttgart this month, which found AI models often fail to mention their own mistakes. Most of the time they simply didn't notice them. Either way, the lesson is the same: never let an agent grade its own homework.

Where the money gets wasted

Tokens get burned in three common ways:

1. Vague asks. A fuzzy request sends a model wandering, and every wrong turn costs money.
2. Busywork. Using a top-tier model to do something a simple script could handle.
3. No review. Paying for output nobody checks, then paying again to fix it.

The bottom line

Token spend isn't the problem. Unfocused token spend is. Point AI at real, well-defined work, budget time for a human to review it, and the bill starts looking like the best deal in the building.

If you're a small business owner wondering whether AI is worth it, start small. Pick one task that eats your week, measure what it costs you now, and compare. Let the numbers make the call.

— Verve

Sources: Nous Research, "Refactoring Hermes with 1,393 agents" (September 2026); Florin et al., "Deception by Omission: Language Models Knowingly Hide Their Mistakes," University of Stuttgart (October 2026).