Hardcore: A Plan to Make AI Work 24/7

1. Pick a cost-effective setup

If your job is mostly copywriting, just use Doubao, Kimi, or DeepSeek (official).

If you need to organize information, handle data, or read a bunch of files, editors like Cursor, WindSurf, Trae, or VS Code with plugins are usually a better fit, because they come with bundled AI plans.

If you don’t care about the process and only want the deliverable—and you want a top-tier model without third-party limitations—use terminal-style tools like Claude Code or Codex.

If Claude feels too expensive, use high-quota domestic bundles like GLM 4.7 or MiniMax.

If you want AI to run 24/7 like I do, but you want the cost low, start with GLM 4.7 or MiniMax. They adapt well to Claude Code’s workflow.

2. Turn your prompt into an asset

If you do the same kind of work every day, try describing the task in plain language.

For example: I want to do xxx. Step one is xxx. Step two is xxx. Step three is xxx.

If your description is clear, send it to AI and see if it can do it better than you.

If the output is decent, that description is already your prompt.

3. Parameterize the prompt

If the prompt works reliably, it becomes your template.

If you notice that copy-pasting still isn’t enough because you always have to tweak a few words, those words are your parameters.

If even copy-paste feels annoying, you can ask AI to generate prompts for you with a script.

For example: I want to do xxx (param 1). Step one is xxx (param 2). Step two is xxx (param 3). Step three is xxx (param 4).

Or ask AI to generate a task list:

• Task 1
• Task 2
• Task 3

In practice, each task is just a parameterized prompt.

You send them to AI in order. Finish one, then move to the next.

4. Auto-send prompts to AI

If sending prompts manually still feels like work, let a program send them.

The old approach is RPA. But tools like Claude Code are basically a command line in your terminal.

So you don’t need RPA here. Just ask AI to write a script that controls terminal input.

Python or Node.js both work.

5. How does your script know the AI is done?

If your script can already send prompts to AI, how does it know whether the AI has finished?

In my own use, the script couldn’t tell, because Claude runs in the terminal, and the script can’t reliably read Claude’s output.

Then it clicked: I only need to tweak the prompt a little.

“After each task, output a result.json that clearly states whether the task is completed.”

That JSON receipt is something a script can read.

result.json)done / artifacts / checks / errorsScheduler decidesAdvance / fix / pausePass → nextFail → fixApprove → pause

6. Add an inspector (optional)

If one AI isn’t enough, add another AI as an inspector.

You can use your scheduler script to orchestrate two AIs.

Why use a “hard-coded” scheduler to orchestrate AI? Because you don’t know how long the AI will take. You need something that keeps nudging it forward.

You can also make it more nested if you want.

AI writes the script → the script commands the AI to work → the AI starts working → the script keeps monitoring result.json → the script wakes up the inspector → the inspector sends feedback to the coordinator AI → the coordinator AI improves the script → the new script makes the worker AI work better…

7. 24/7 self-feedback

Infinite loop.