I kept seeing the same pattern in my own work. The bill was never the first problem. The first problem was that I did not know what I was spending while I was spending it.
That sounds obvious until you live inside it.
You open a model, test a few prompts, switch tools, paste more context, retry, compare outputs, and keep moving. The work feels small in the moment. Then the invoice lands and the number looks irrational.
What surprised me was not that AI cost money. It was how little feedback existed while the money was being spent.
That gap changes behavior. If you only see cost at the end of the month, you are managing a report. If you see cost while you work, you are managing a system.
That is why I built TokenBar.
TokenBar is a macOS menu bar app that shows live token usage and spend so you can catch waste early. Not after the bill. Not in a dashboard you check later. Right there, while the session is still active.
The goal is simple:
- catch runaway prompt loops before they turn expensive
- make model choice a live decision instead of a vague preference
- show which sessions are actually costing you money
- keep the feedback where the work happens
The big lesson for me was this: AI cost control is mostly a UX problem.
Most people do not need another dashboard. They need frictionless awareness.
A dashboard asks you to remember to check it. A menu bar app reminds you automatically.
That matters because the waste is usually not dramatic. It is death by a thousand tiny mistakes:
- too much context
- too many retries
- the wrong model for the task
- a debugging session that keeps running because nothing tells you to stop
I built TokenBar for the same reason people keep a battery icon visible. Not because they love metrics, but because invisible drains get expensive fast.
If you work with LLMs every day, live cost visibility changes how you ship. It makes you ask better questions before you hit send.
Do I need the expensive model here?
Do I really need that much context?
Is this session still worth continuing?
Those are boring questions. They are also the ones that save money.
TokenBar is for people who want that answer in the moment, not at the end of the month.
If that is you, take a look:
I am curious what others are seeing too. Are your AI costs a pricing problem, or a visibility problem?
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