I blew through 24 million tokens in a day - blog.kronis.dev

I blew through 24 million tokens in a day

Date: 2025-10-20

Suppose I have a legacy project, or even just an older project that I worked on previously and now want to carry over the mechanisms that made it work, to a new one.

All sorts of custom functionality, wrappers around the underlying library components with custom functionality, like being able to tell when any input field or input element has been touched and a form should be considered dirty (prompt before navigating away), as well as links and navigation logic that integrates with this, custom utilities for i18n built on top of pre-existing solutions, validators, date and number formatting utilities (maybe with moment.js and currency.js integrated) and so much more.

There might be dozens, or sometimes hundreds of files in a project that otherwise has over a thousand source files, obviously not coupled as loosely as it might be (e.g. a collection of separate packages), because clearly nobody has the time for setting that up and that's never how these things evolve over projects that span 5 or more years.

Yet, I don't want the business functionality. I don't want the constants from that project. I don't want the router routes, but I want the logic for having nested routes, I want the logic for highlighting the route group in the navbar/sidebar when a route below that is active, I want at least some of the permission checks and the more generic bits of redirects to the login page, error handlers and error boundaries and so much more.

You'll notice that this example is front end centric, but it might as well be back end centric as well. In either case, what I have a lot of are requirements, since otherwise I'd be writing everything from scratch and that never works out well, especially when there are perfectly serviceable implementations somewhere for me to reference, instead of rediscovering the edge cases anew. But maybe I want to migrate it all to TypeScript, maybe I want to move from Vuetify to Quasar, perhaps I even want to explore implementing the same functionality with Pinia, or get rid of it.

The one thing I don't have, however, is time. Nor do I think I necessarily have enough motivation or working memory to go through 100 components and update all of them in a specific way. Everyone has deadlines and even if it's a personal project, the evenings are only so long. So, it's the perfect use case for generative AI, right?

Generative AI and its main problem

Well, sort of. Having generative AI at your fingertips does a few good things:

it follows boilerplate adjacent tasks pretty well

even more so if you can give examples of what to do and not to do

furthermore, whatever it spits out isn't too hard to verify as correct/incorrect

it doesn't get tired and demotivated, you can also steer it in a particular direction easily

In other words, it's like having a very motivated junior developer that sometimes does completely erroneous things, but at the same time has like no ego and will carry out your bidding, which you will never get with real human beings (nor should you expect that). In other words, it's a tool.

Unfortunately, hundreds of files is still a lot, even for most of the AI solutions out there. Not if you're swimming in money, like 1000 EUR a month to spend on it and above, as these people did a while back:

Frustrated [with the LLM-isms, like changing failing tests into skipped tests, overcomplicating changes, unnecessary dependencies], I tried switching from Claude Sonnet to the new o3 thinking model. I knew o3 was painfully slow, so I took the time to write out exactly what I knew, and what I wanted the solution to look like, and gave it some time to work. To my surprise, the response was… great?

The more I tried it, the more I found o3’s improved ability to use tools, assess progress, and self-correct led to results that were actually worth the wait. I found myself expanding what terminal commands I allowed the agent to run, helping it get further than ever before. When I completed a hard “o3-grade” task and moved on to something simpler, I was increasingly tempted to leave it on o3 instead of switching back. Sonnet was faster in theory. But o3 was faster in practice.

The only problem was, it was costing a fortune.

Depending on the task, my o3 conversations were averaging roughly $5 of Cursor requests each, or about $50 a day. That… is a lot of money.

Still, we were in a hurry. And what is a startup if not a series of experiments? So I turned to my co-founder.

A: Jenn, I have a proposal. You’re going to hate it. ... So you know I’ve been getting really good results from o3. I propose we try just defaulting to o3 for the next 3 weeks until our demo, and increase our Cursor spending cap to $1000/mo.

B: That’s a lot of money.

A: I know. It’s ridiculous. This is ridiculous. But also, when we hire a Founding Engineer, they will cost a lot more than that. Like,...