A developer just shipped a tool called LLMCap and it hit the front page of Hacker News. The pitch is simple. It's a proxy that sits between your code and the OpenAI API, and when you hit your dollar cap for the day, it hard-stops every call. Brutal, but it works.

They built it because their AI bills kept surprising them.

If you're a developer, you can install LLMCap and sleep better. If you're not a developer, you can't. You don't have API keys. You don't know where the calls are coming from. And that's where a lot of people who want to build with AI right now are stuck.

So here's the version for everyone else.

Why AI bills go sideways

One call to GPT or Claude is cheap. The problem is that modern AI apps don't make one call. They make hundreds.

An agent calls a tool. The tool calls another model. That model retries on a timeout, and the retry uses a bigger context window. The user types again and the loop starts over. Nothing looks wasteful in isolation. Stacked up, you can burn a hundred bucks before lunch.

For developers, the answer is building cost controls. For non-developers, you need a different approach. You shouldn't have to write a proxy.

What to look for in a no-code AI tool

A few things to check before you commit to a platform.

Credits or raw API billing? Credits are a flat unit you can budget against. Raw pricing means you're exposed to whatever the model providers charge this month.
Can you see what each action costs before running it? If a button can charge anywhere from 10 cents to 30 dollars and you only find out after, that's not safe to ship on.
Can you set limits? Monthly cap, per action cap, anything.
Are you paying for idle infrastructure? If there's a workspace fee that runs even when you're not building, costs keep compounding when you step away.

These are not technical questions. You can ask them on any sales page.

How we think about it at DontCode

I won't pretend this is solved. But on DontCode, the rule is that you never get an API bill from us. You buy credits, you spend credits, and when they're out, the work stops.

Our AI is fine-tuned for app building specifically. That sounds like a marketing line but it actually means we get more done per call than a generic Claude or GPT wrapper. Fewer retries, fewer wasted tokens, lower cost per feature shipped.

You don't manage keys. You don't proxy anything. You don't pick a model. You describe what you want and the platform figures out the cheapest way to do it well.

If you want to try it, you can start here. If you want more for non-technical builders, the blog has more in that lane.