AI Coding Plans: How to Stay Within Your Limits

If your AI coding plan runs out by midweek, you don't necessarily need the most expensive tier. Often you just need to stop using the best model for everything. Here's how to split work between a strong model and a cheap one, and what to do when you hit the limit. You set it up once, then follow it every week.

What It Is

It's called cost-aware routing: for each task you pick the model that's good enough, not the strongest. Critical work goes to the best model. Simple, repetitive work goes to a model that costs much less. And when your main plan hits its limit, a fallback is already decided.

Why It Matters

It happened to us. The way we work with AI agents had started going over the weekly limit of our Claude Code plan. Instead of just buying more capacity, we tested other providers for non-critical tasks: DeepSeek, Kimi and Qwen, through a single gateway, meaning one access point that talks to several providers in the same way.

On analysis and documentation tasks, in our test, quality was above 85% of Sonnet's, at about one twelfth of the cost. Since then, this split has been a fixed part of how we work.

The lesson applies to you too: loyalty to a single provider is a luxury. Picking the right model for each task becomes a necessity as soon as AI is part of your daily work.

How to Do It

1. See where your plan goes. For one week, note what you use AI for: writing new code, fixing bugs, explaining files, writing docs, summaries. A simple list is enough.
2. Split into critical and simple. Critical: code going to production, customer data, security, hard decisions. Simple: analysis, documentation, summaries, first drafts. That's where, in our test, the cheaper model held up.
3. Try a cheaper model on simple work. Give it five or ten tasks you've already done with the best model and compare. You decide whether it's "good enough".
4. Set up the fallback before you need it. Write down today what you do when the plan runs out: which model you use, for which tasks, and which tasks wait for the reset. No improvising on Thursday night.
5. Set a spending cap. If you pay per use, set a monthly budget and an alert in the provider's dashboard. Plan limits and prices change often: check your own account.
6. Review the split every month. If a "simple" task keeps coming back with errors, move it to critical.

Ready to copy. Paste this into your AI assistant, followed by your list of tasks for the week:

And this one for the comparison in step 3:

A Sample Split

For a small studio that builds websites, the split could look like this:

• Best model: new features, fixing production bugs, anything that touches payments or customer data.
• Cheaper model: explaining how a file works, writing docs, summarizing a discussion, a first draft of some copy.
• Fallback when the plan runs out: all simple work moves to the cheaper model; critical work waits or is done by hand.

It's not a fixed rule. It's a starting point you correct with your own results.

Try It Small

Take a simple task you've already done with the best model, like summarizing a file or a page of docs. Redo it with a cheaper model, same prompt. Put both answers into the second prompt. In ten minutes you'll know whether that kind of task can move: if you'd use answer B after a small fix, it can.

Watch Out For

• Our numbers are ours: the 85% and the one-twelfth cost come from our test on analysis and documentation. Run your own test on your own work.
• Where your data goes: before using a new provider, read where data is processed and the terms of use. If your data can't leave, read when local AI is worth it.
• More models, more to track: keys, accounts, invoices. Start with two models, not five.
• Savings don't apply to critical work: there, a mistake costs more than you save.

To choose your main model, read how to choose an AI model for your business.

In short: Choosing the right model for each task matters more than choosing the best model overall: the best one gets the critical work, a cheaper one gets the rest.