Comment by esperent

12 hours ago

On the other hand, I did just leave my pi agent running GPT 5.5 overnight on a clearly defined, long running task. It's been running about 10 hours now and it's mostly done. So this kind of use case is also valid.

Thinking about it, I would say that the majority of agentic work I do, by a long shot, is subagents which are launched from the main session, using a prompt of its choosing. Those could be considered short versions of these fully autonomous tasks.

Care to share more about your pi setup? I've recently started using it (after long-time Claude Code work) and was wondering how you'd achieve these long-running tasks. Do you allow it to spawn sub-agents? Thank you!

  • My pi usage over the past ~5 months went roughly like this:

    * Install pi and a bunch of extensions from their package repo

    * Realize that all the packages (with a few exceptions) are massively overcomplicated and vibe coded

    * Ask pi to rebuild a very simple version of the packages I used. So e.g. subagents - all the default subagent extensions are massively complicated with named agents, recursion, communication. I made one that stripped all that out.

    * Then whenever I hit an annoyance, spin up a parallel session and fix it.

    It's less work than it appears because I have ~5 extensions: hooks, subagents, background processes, a custom footer, a loop command... Maybe that's it. Within a couple of days you can have a setup pretty close to Claude Code but with a fraction of the base context use. After gradual improvements over a few weeks/months you'll have a system far better, tuned to your exact preference.

    Of course, just like Linux or any other highly tunable system equally important is having the restraint to not spend all your time tuning it. I've definitely had a couple of days where I was bored with my real work and did that, but whatever, it beats browsing reddit.

    As for getting long running tasks, I set a looping message every ~20m and tell the agent to strictly track progress in a session doc, then reread and continue after each compaction.

    • I'd like to study your setup. Would you be willing to share? Perhaps a github repo of your 5 extensions or even a pastebin if you would be so inclined. I would be grateful to learn more about this by studying from your success...

    • What type of task are you running for ten hours? Is this a programming task?

      I've not come across a programming task that would take an LLM ten hours.

      1 reply →

Yes, part of the reason I chose the one-shot test was really to test long-running tasks. A lot of people seem to be experimenting with this format, for example in the now trending loop-writing workflows. And really I am interested in diving into the murky waters of these novel workflows.