I don't use Pi very much for actual writing code. I have some specific use-cases where I do, but I'm admittedly just not a person who can reasonably juggle a lot of tools or a super personalized setup. I mostly just use Codex or CC from the terminal, though I've recently dabbled with some GUIs. Basically, once I find something that works, I'm pretty reticent to spend any time tinkering unless I feel a real need.

But what I do use Pi a lot for is as a base for agents. I much prefer it to using an agent SDK. I find its minimalism and extensibility to be a really nice substrate for new projects.

I could easily imagine someone getting to a really productive personal setup with it as well, for the same reasons as above.

I am using pi the same way everyone uses Codex and Claude, but pi makes it very simple to make folders to make the agent behave a certain way and that was easy for me to understand.

ChatGPT Desktop seems to intentionally hide what they are doing and where they are storing state, sessions, config, I never had any idea what is in context or what "archiving" even means. I got sick of OpenAI hiding how ChatGPT Desktop was working. I opened pi and the default behavior shows me how much context I am using, how much that costs and tells me where it stores my session data.

Suddenly it was all demystified and that is why I use pi. It has nothing to do with a functional gap, it was the joy a using a harness that was transparent about how it worked.

Don't give into FOMO.

Developers just love to spent considerably amount of time and effort into building tooling. Way more than working on the actual products.

But I must admit it is really fun to build your own harness and tweak it to your liking, even if it is never used for professional work ;-)

Writing my own harness with the workflow I prefer. I pull jira tasks in local task manager(aven). My harness will oneshot it or create a spec plan with multiple linked tasks. Implement it with creating git worktree, task by task, codereview with 2 different reviewers, PRs it, reviews peoples comments replies or fixes and check sonarqube and fix if needed.

Manual tests in my minikube and has skills to deploy the right service there. It updates the jira ticket with test proof.

For debugging flows I build skills to use my local minikube that has our full dev environment and all services running. Can debug there. It has grafana skills for gcx can grab logs and through grafana even accesss dev/staging db for quering.

I wrote all the extensions with these custom integrations. It works just like I would work... I don't like adapting myself to another opinionated harness. I prefer my own opinionated workflows.

I've only used it at home a little on personal projects. My usage is probably odd -- I connected it with Bedrock, but otherwise used it the same as I do Claude Code (mostly). My basic flow was simple:

  - Ask it to accomplish some coding task
  - If it fell short, and I determined that was due to the harness, ask it to patch
  - Otherwise proceed to next task
  - Rinse + repeat

I run it within a sandbox, so I've been comfortable with the lack of native "approvals". So far my personal usage hasn't really needed subagents, but I think this is one thing I'd need to sort out were I using it professionally[1]. I'm aware of oh-my-pi, but I think half the fun is hacking from the base.

The light weight prompt and simple harness design are a lot of fun. I don't mind Claude Code, and I think its well designed for the problem domain, but Pi is a lot of fun to hack with.

Hope that helps!

[1]: https://mariozechner.at/posts/2025-11-30-pi-coding-agent/#to...

I use PI WEB (https://pi-web.dev, there's more than one with that name) to orchestrate remotely. Pi lets me run local models (currently Qwen 3.8 Flash Next on Strix Halo 128GB) and flagship models (with subscription auth, not API pricing) side by side. I typically ask GPT 6.1 Sol to review requirements and then spawn a subsession with Qwen, review Qwen's work, ask Qwen to fix. About 95% success with a single pass like that, achieving flagship quality without the price tag (albeit slower).

I started using Pi because it has a small system prompt and local models were too slow to start. Then I started adding custom skills and extensions when I hit little corner cases. It's been so easy to bend into what I need.

I’m also looking for tips. I feel like I get the gist, but if I sat down to use it, I don’t know what I want to start with. Like, I know it’s customizable, but what’s the on-ramp so I can figure out what that looks like?

I use pi with a ChatGPT subscription. I find that it does better than the native codex harness: - it's very token efficient. I've had whole profiling + refactoring sessions finish in <20k tokens, whereas in codex you can get close to that with just all the cruft OpenAI loads by default before you even send your own messages - the token efficiency means turns are a lot snappier - fine-grained context control by default - I have to disable a bunch of stuff in codex so it doesn't pollute my context with generated memories - I find that OpenAI model sometimes struggle to navigate codex' sandboxing, and burn a bunch of tool calls retrying outside the sandbox when the sandboxed command fails

I believe this is the popular "batteries included" kit: https://github.com/can1357/oh-my-pi

It's been pretty useful for experimenting with local models due to its more light-weight approach. Though I respect the creators a ton, OpenCode has not seemed to work as well with models that run on consumer hardware

I use claude code and codex in a terminal like a caveman too.

then i use pi in a terminal like a caveman to try the open models like deepseek etc.

I also have pi running on a VPS. I have a custom Django app that calls out to it for a bunch of stuff. I don't know how the full system works because the agents built it but basically I think one pi uses a whatsapp wrapper to constantly listen to a whatsapp group and find bills. Then those get added to the Django Database which triggers a second pi + deepseek to OCR them, parse out the data like amount, due date, reference etc, and update the database with that. I have a trigger to 'merge duplicate', which is also just a prompt and pi.

Yes you can do all this without a harness and just the model APIs directly but the harness means it can use linux tools to crop the PDFs etc, so when I also wanted a new feature that crops out the bank details and lets me hover over and see the original before making the payment for a bill that's just another tweak to pi's prompt (or more meta, me prompting my agent to update pi's prompt).

I've been using Pi almost exclusively as coding agent in various forms since more or less January this year (I think). I settled quickly for a short list of extensions (which I wrote and I maintain) and a few skills/shared AGENTS.md, also installable as extension: https://forge.l3x.in/alex/pi-shared

For one thing I've re-built my personal website with it (mostly via GH issues from GH iOS app) and also added a section to talk about how I use AI in general: https://a.l3x.in/ai

I also maintain a couple of other Pi-related projects:

- https://awesome-pi.site/ - https://github.com/shaftoe/pi-coding-agent-action

So yeah, I still love the tool and use it pretty much every day, either as TUI sessions or inside CI/CD workflows.

Long live Pi!

I use my Pi to organize my graphic design assets as well as update documentation for client projects. It also is my daily driver for a story I'm working on and thanks to a ton of great skills created it has become more powerful. Local model is Qwen3.6 35B-A3B and Qwen3.8 27B UD. I love the compressing function, keeps on pushing.

I've tried Oh-my-pi but it's too heavy for me and eats up 6% of my context on start. Also I find Pi's keyboard shortcuts easier to use.

I use WSL, one tab is GitBash running llama.ccp and the other is normal terminal running pi. Winning combo for me.

Also started using Pi as my search engine, which I've refine and does what I need it to do, can also ask it to create a html doc with links or markdown. Fun stuff.

Pi is the "I use arch btw" of harnesses right now.

But I do love it - super customizable, and my token usage seems way more efficient (this is purely vibe based ofc) compared to codex/cc.

I basically just install pi-fabric, pi-blackhole, grill-me and that's it. Tell my AGENTS.md to prefer subagent workflows. Herdr to manage all the terminals. I spend 99% of my professional work in this environment, I can't even remember the last time I had to open vscode/nvim.

I use Pi in the terminal and with Zed (with its "right hand side" terminal bar you can make its agent panel do), and I use it with Pendant in VSCode at home: Pendant is really quite impressive, I'll be honest.

I mostly use Pi, with the small exception of using Claude for some more intense coding projects. But for everything else - homelab playgrounds, data stuff, really almost anything else - it's Pi, and I'll probably move my code work there, too. I have a handful of extensions that I like and make it more useful for me, and really like the simplicity of the TUI over some of its competitors.

You just type "pi" in the command prompt and you're good to go!

The only thing I've configured is the default model.

I've put it into an XMPP wrapper for all communications so I can talk to my agents from any device supporting XMPP (all devices). This also means agents can talk to each other using group chats. I'm building apps from my phone on the bus, and handing off server admin tasks to the agents since they run in their own NixOS account with limited permissions.

I built https://rcarmo.github.io/projects/piclaw atop it. It's pi, but with a web UI I use every day, across dozens of agents, and has pi-based add-ons. I do use the TUI on occasion, but need a remote web UI for 99% of my stuff.

Ten people have replied to your question (which is the same question I have) and not one of them have answered it so I figured I’d be number 11.

Like, is this thread full of astroturfing bots? What am I reading

I'm running it on a docker container that only has mounted a folder from the host os. been playing around with godot and blender. still looking for a good workflow, but pi is lovely.

Pi is popular for local-models/alternate-models. It's not much different from Claude Code and Codex otherwise.

I use Pi with only a couple of extensions and using less and less of CC and Codex everyday. It feels light and nimble. Codemode from yesterday's release made it even better. I wish I could use my Claude subscription via Pi.

I built and “ide” around it in obsidian. Works great. And I don’t need to jump between apps to change models. Astra and opus in same chat works just fine

Absolutely. Fellow caveman here, and a fan of Pi. I often use it with Astra instead of Codex, because its extensions allow you to connect it to the world. And it works very well.

I built my own based off another popular harness. I figure most of the edge cutters are doing the same.

Pi is great overall. I ended up deploying a GUI wrapper because TUI isn't as friendly to new adopters.

Vanilla Pi is great. I have a subagent/ Ralph loop extension I coded and that's basically it. It works very well. I'm about 75% pi, 20% autolith, and 5% my own harness

Exactly like that. Just install it, connect a provider and do stuff.

You don’t need extensions or fancy setups.

> Here I am with Claude Code and Codex in a terminal like a caveman

There's definitely a class of folks who like to "polish their tools" per se vs tools just being as a means to an end.

It's fine and cool, sort of like the desktop ricers do with Hyperland, Niri, etc showing off desktops, but never seem to do anything with this cool tech.

Using models from multiple providers via aws bedrock

Pi with Caveman Plugin :D

I use workmux with pi plus some neovim plug-ins

Pi vs opencode for example is like gentoo vs macos, if you want to spend your time customizing and dealing with harness itself rather than doing the work, then go for it, it will be fun, like gentoo. I think the best productive setup is herdr+opencode or zed and opencode, unless you need CC for anthropic models. The only thing however, is how the same model works with different harnesses, positive or negative, is where you might need to shuffle between to maximize the results.

Frankly you are not losing much. I've used everything under the sun, for work and fun. I just use Claude now again for work, and I use Pi for any openrouter model I'm using.

Just keep using Claude or Codex.

It's all window dressing and some delta in token usage, but again who cares really?

This really only matters when you're productizing "AI" for your end users, that's when you need to see which agent uses tools better, has more support for MCPs, headless mode, sessions, etc. \

the main thing i use it for that seems like a pain with other coding agents is my sandboxing workflow: i have a custom extension which allows the pi process to run on my laptop, keeping all my transcripts in one searchable place, while delegating all the bash and file system commands to a VM.

i haven't gotten around to it yet, but i'd also like to change how `Bash` functions on a basic level (and subagents), where rather than the agent picking a fixed timeout, it just gets notified with exponential backoff about commands that aren't done and then gets a turn to decide what to do with it.

having said that, i find it annoying and not empowering that basic things like subagents and web search aren't built in. the ideal to me seems to be an agent with polished extensions for all the common use cases that can be disabled if you do want to rewrite them. but i put up with the pain because i really want my pet feature ¯\_(ツ)_/¯

I use it headless for reviews in CI.

They are not, Pi is the vim or mechanical keyboard of the pre-AI era. Didn't matter then, doesn't matter now. Will generate infinite discourse regardless.

Extensively, almost as much as I use my editor.

I have eight or nine custom extensions at varying levels of maturity, some nearing the point where sharing them becomes useful.

One is a simple but obvious Eoka extension for Pi.

I modified my terminal (Alacritty) to support the Kitty image protocol (it already spoke sixel; Pi understandably uses the superior Kitty protocol). And a toolcall that lets the LLM put an image in the transcript (upstream Pi lets only image-modality LLMs do this). "Deepseek, do XYZ in a headful Chromium using Xvfb and show me a screenshot before each step".

Once you see the immense power you get from being able to modify both ends of the terminal connection (and having LLMs write the tests and tedious parts for you) it's addictive. I've added a custom terminal extension for negative-row-number cursor positioning, and support for it on both sides of the connection (Pi and Alacritty). End result: all the performance of native scrollback with no compromises -- Pi can modify rows above the top of the visible part of the screen, like collapsing/expanding toolcalls, without forcing a full-terminal refresh.

Also: click-to-expand/collapse toolcalls/replies individually. Really helpful.

Disappointed that Pi is abandoning the minimality philosophy.

And you're probably more productive than the people using Pi. Although you'd be even better off using a GUI agent multiplexer of some kind rather than juggling terminal tabs.

I love open source. I love the terminal. I spent the last 20+ years in a terminal w/vim every single day, and then claude/codex TUIs, and yet I care more about my own productivity so I don't use any of that now.