Operations: The Cost of Every Click

In traditional software, once the code is written, it doesn't cost much more to support one thousand users than it does to support ten. A platform is built once, and the resources to run it are relatively cheap. With AI, that math changes. Every time a user interacts with a system, it requires a significant amount of computing power. In a very literal sense, every interaction has a cost attached to it.

If a system runs every simple task—like sorting a list or finding a date in a document—through the most powerful models available, the costs can quickly outpace the revenue. To make a product sustainable, builders have to be smart about how work is managed. This is often handled through a tiered approach. When a request comes in, it can be evaluated to determine how much computing power it actually needs. Simple tasks go to smaller, faster, and much cheaper systems. This saves the heavy-duty, expensive computing for the tasks that actually require deep reasoning.

Efficiency is the difference between a product that is a curiosity and one that is a viable business. By matching the complexity of the task to the right amount of computing power, a system can remain fast and responsive without becoming prohibitively expensive to run. This approach ensures that as a product grows and handles more users, it stays efficient. It is about building systems that don't just work well, but make sense on a balance sheet.