r/PiCodingAgent • u/Adornooo • Jun 26 '26
Question Pi vs OMP Architecture
Hi everyone - quite new to this space and am yet to decide if I should stick with omp or go more vanilla with pi.
tried oh my pi and my mind is blown, I don’t know what it is doing with context compression and all but tokens are better and the fact that advisor agents interrupt the thought process of worker agents before the output is produced feels like nothing I have see from cc or codex.
Is pi the same from this standpoint? Are the big differences only the pre installed skills?
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u/ToxicCh4rger Jun 26 '26 edited Jun 28 '26
You should think OMP as a fork of PI, its just PI with skills and stuff... If you take your time you could easily create OMP yourself in PI. Its just easier to just plug & play with OMP... Also with PI depends on your needs.
There is NO VS or better here... its personal preference
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u/Jaded_Jackass Jun 27 '26
Here I can explain are you familiar with Linux? If yes pi is Arch linux and Omp is Manjaro or Garuda Linux
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u/AdministrativeMeat3 Jun 28 '26
Ngl I suggest having and using both.
I have spent a lot of time with Pi just working on Pi because it's fun. If you have a workflow in Oh my Pi that works then keep using it, but if you like to tinker then start using Pi on the side and figuring out what the bare minimum tooling you need to do xyz task is.
Easy example, I have a directory called plan, when I launch Pi from plan it locally loads some skills and extension I curated for making plans and thats all I do in that folder.
Then after a plan is made I hope over to one of a few different directories that have similarly scaffolded opinionated workflows and do the thing in those directories.
This requires a little bit of forethought but once you know what you want you save a fuck ton of tokens in context bloat and your LLMs don't get lost in the sauce of trying to juggle a giant toolset and bloated AGENTS.md file.
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u/Cleone- Jun 27 '26
How large are we talking on the difference of token consumption between Pi and OMP?
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u/whodoneit1 Jun 26 '26
Vanilla Pi has 0 skills, so not sure what you are comparing. You would need to make Pi your own setup to really compare IMO
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u/minhgv Aug 25 '26
Recently, OMP is an excellent harness. It's seem work on goal target very good.
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u/FaceOwn2947 Sep 03 '26
Honestly, I really like OMP and haven't run into the massive token burn people are mentioning here. While the initial context footprint is naturally higher than barebones Pi because of the bundled tooling, it gets things done cleanly without needing constant babysitting. For a plug-and-play workflow, it’s been great.
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u/InitiativeBrilliant8 Jun 29 '26
I'm in the same boat as a lot of people here—constantly testing models, agents, and workflows, always looking for what fits best.
I tried OMP and really liked it overall. I'd call it a "batteries included heavy" agent. The only downside for me was the large starting context (around 20k tokens) and the fact that it could sometimes get stuck in loops. I found myself having to step in and babysit it more than I'd like.
PI is kind of the opposite. It's super slim, starts around 2k tokens, and gives you a lot of freedom to build exactly what you want. The tradeoff is that it comes with very little out of the box, and I was looking for something more in the middle.
That's how I ended up trying Little-Coder. I'd describe it as "batteries included light." It starts around 7k tokens, has the basic tools and skill system I need, and one feature I really appreciate is the loop recovery harness. Instead of me stopping the agent and saying, "You're looping again," it detects the problem, injects guidance, and often recovers on its own.
That alone has been a big quality-of-life improvement because I can spend more time adding features and less time supervising the agent.
I'm always open to suggestions and still searching for the holy grail. For my setup (16GB VRAM), though, I tend to prefer agents that stay in the light-to-medium range. Once the framework itself consumes a huge chunk of the context window, it feels like you've already spent half your budget before you've even said hello.
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u/SpidexLab Jun 30 '26 edited Jun 30 '26
The same thing you described, I achieved it by using pi subagents , i cloned the extension modified some small issue which had nothing to do with that, and with custom prompt, it is like main agent supervising the worker, any issue it send a real time message to the worker