How can you operate a more serious system from the limited weekly budget of the Codex Plus package? I'll tell you!
How can you manage a more serious system with the limited budget of the Codex Plus package? I'll tell you!
No, this was not written by an AI. There are many other posts now. I am a person who operates a fairly complex content production system and many other small processes with the Codex Plus package. By the end of the week, 55-60 percent of the weekly package remains. This may seem like magic to many of you, but it's not.
What do I do?
Openclaw is in an executive role for me. It writes code, but not much. Its main task is to monitor processes, troubleshoot errors, and implement completed capabilities into the finished system.
Almost all of the tasks run Python scripts. This is good for two reasons. First, it is good for tasks that do not require the AI token. Second, the script output is stable and regulated. The AI's role here is to supervise execution and send a one-word Telegram message about the result. If there is an error, it indicates that the run has stopped. In this case, I check what the problem was—it also describes the problem—and, if necessary, I provide instructions for the solution. Most of the time, I don't need to provide instructions because it suggests a fix. I approve the suggestion, and it fixes the problem. But only if I approve it.
I should mention that I have both a coding agent and a reviewing agent. The main agent gives the coding task to the coding agent, which forwards the finished fix to the reviewing agent. If the report is flawless, the reviewing agent sends it to the main agent, who incorporates the fix. This may seem redundant, but it saves time and tokens because the completed codes and fixes are always flawless and work the first time.
The Python code used for the operation was written by Claude in the desktop application. I didn't use Claude's code either; the tasks were short, and it was fine without it. Now, OpenAI also writes code in the desktop application. This feature is included in the $20 package, so I don't use Openclaw. Previously, I would throw the completed code into another AI application to have it checked. Recently, though, I haven't needed to do that.
I save money by inserting the Python code created with the web application into the system and instructing my agent to review it. If an error is found, an error log is written. If no error is found, the code is integrated into the existing processes.
If an error log is generated, I return it to the desktop application, which then fixes the code based on the log.
The point is that the Openclaw agent's job is not to write complicated code but to make the system work.
There was a weekly batch reset this morning. I had 42% remaining when I switched from 2026.4.23 to 2026.5.3-1 yesterday. That took a lot of tokens because of a configuration bug in openclaw.json that prevented me from using the Codex 5.3 model after the upgrade. I didn't want to waste tokens on this since 4.23 was working fine. However, last night, I had 54% of my weekly token allowance remaining, so I switched to GPT 5.5 High. This solved the configuration problem. Now I have a fresher system and saved a lot of tokens for this bug fix. However, I still wasted over 40 percent of my weekly allowance because there was simply nothing else I could have used them for.
I wrote all of this so you can see that even an extra $20 package is not a small amount to operate; you just have to use it wisely.