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Comment by esperent

10 hours ago

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.

  • I'm not the person you asked, but if they're running in their own local hardware, then it might just be a lot slower than what the big providers run their models on. System RAM is a lot cheaper than VRAM, especially if you bought it last year.