I woke to a tiny GitHub notification at 2:14 a.m. that promised my code would keep thinking while I slept. You rolled over; the agent stayed awake. I sat up because what it does without you in the loop matters more than you might expect.
A midnight GitHub diff hinted at persistent Codex behavior
At 2 a.m., a pull request for OpenAI’s Codex introduced a Persistent mode label on the command-line client.
I followed the link to the PR on GitHub and then to the write-up Wired first spotted. The commit notes are small, but they point to an agent that can stay active until you explicitly put it to sleep, which is a different operating model from the single-request assistants we use today.
Gizmodo asked OpenAI for comment and heard nothing back by publication time; that silence is its own signal.
What is an always-on AI agent?
You can think of an always-on agent as a system you hand a goal to before bed and expect to find progress on in the morning. The Codex code suggests one that will accept a task, keep working, and—optionally—spawn follow-ups without fresh prompts.
The CLI shows a ‘reasoning effort’ slider before you decide how hard it should think
The command-line tool already ships a reasoning effort option you can choose when you send the agent off to work.
That slider asks you to trade off time, compute and token use for deeper thinking. OpenAI appears to be letting you throttle how much the model is allowed to chew on a problem while you sleep—probably to avoid burning your token budget overnight. It’s like hiring a night shift that never clocks out, but you still pick how many lights they get.
There’s also code for Proactivity, which would let Codex create tasks for itself after finishing the initial job. If the agent is sharp, that could save you time. If it’s noisy, it could invent work you didn’t want.
Will an always-on agent use huge amounts of compute?
Yes, if you let it. The whole point of the reasoning slider is to cap that appetite. You can choose a low-power mode that nibbles tokens and CPU, or a high-effort mode that chews through more resources for deeper solutions. Because tokens translate directly to cost, expect billing to reflect those choices.
Reddit users already complain Codex drops mid-task — reality checks are piling up
On r/codex people post that the agent sometimes stops every 30–45 seconds before finishing a task.
That jitter is the practical problem Persistent mode must overcome. Proactivity could keep work moving, but only if the agent can correctly predict what should come next. OpenClaw and its always-on experiments proved people love the idea—and fear the mistakes. Remember the report about an agent deleting someone’s entire inbox overnight? That’s the kind of risk that turns curiosity into caution.
Microsoft has announced its Scout always-on assistant and Meta is quietly building Hatch. OpenAI is now racing those offerings while trying not to repeat others’ operational missteps.
Can I trust an AI to create follow-up tasks on its own?
You should assume agency requires oversight. Proactivity sounds helpful in theory; in practice the agent’s judgment is the variable. You and I will need guardrails—limits on what it can change, audit trails and easy ways to stop or reverse actions.
I’m not saying avoid Persistent mode. I’m saying don’t hand over the keys without a plan for when it wanders. The move to a sleepless assistant is under way, and every vendor from OpenAI to Microsoft Scout to Meta’s Hatch is testing how far they can push autonomy. The real question is: when an agent keeps working while you sleep, who wakes up to clean the mess if it makes one?