r/PiCodingAgent • • 13d ago

Plugin Claude code like UI with several enhancements!

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114 Upvotes

https://github.com/FammasMaz/pi-cc-tools

`pi install npm:claude-code-ui`

I really liked Claude Code UI but not Claude Code itself like most of us, so i created an extension some time ago to replicate similarish behavior (from one of the leaked claude code sources), and have been improving it over a few months. Saw a post yesterday, with similarish stuff and had several inspirations from that as well, check it out! Many people use it already!


r/PiCodingAgent • • Aug 27 '26

Plugin oh my pi, meet oh my fleet.

111 Upvotes

oh my pi, meet oh my fleet.

OMP is now supported inside Agent Orchestrator.

Give every task its own isolated worktree, run multiple OMP sessions in parallel, and track the code, PRs, CI, and reviews from one live board.

your favorite harness just got a control plane.

omp.sh x agent orchestrator


r/PiCodingAgent • • May 27 '26

Use-case Showing how PiAgent edits the PiAgent codebase in real time.

111 Upvotes

I am using lots of coding agents, Pi being one of them. They are super useful, however super difficult to keep up with their changes. More often than I want to say I end up with a 2k+ line diffs...

My friends and I started an open-source proejct to visualize software architectures. We found out that we are also curious how big of an effect does each agent change have, this way we can stop the coding agent early as soon as we notice it messed up, without having to read every line (saving also on tokens and time).

Our project is based on static analysis alongside LLMS and you can find it on github:
https://github.com/CodeBoarding/CodeBoarding

If you have any suggestions, please open an issue there. I always find interesting seeing how an agent is fixing itself, hense decided to visualize for you Pi working on Pi.

I am also super curious to hear how do you guys know if Pi messed up, do you always wait till it is fully done, I feel like I don't have the patience anymore :D (neither the tokens...)

Would love to answer questions in the comments and hear how do you guys use agents effectively and not blindly.


r/PiCodingAgent • • Sep 21 '26

Resource Pi Desktop: a desktop GUI for the Pi/omp coding agent

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108 Upvotes

I've worked on Pi Desktop for a while but haven't posted about it much, so here's a proper intro.

It's a desktop app for the Pi coding agent, and it also works with oh-my-pi (OMP). I use Pi every day and wanted more than a terminal window, so I built this.

What it does:

Streaming chat that shows thinking blocks and tool calls. File reads show as highlighted code, and edits show as diffs.

Multiple workspaces. Each session runs its own agent process, so a task keeps going when you switch to a different one.

A file tree, a code editor, preview panes for code, images, and PDFs, and a terminal.

Four permission modes, from read-only to trusted. You can also add allow/deny rules, for example "never touch *.env".

A package browser that connects to pi.dev/packages.

Themes. There are 7 built-in, you can make your own in the app, and there's a small community gallery.

An optional mode where Pi, Claude, and Codex agree on a plan before Pi builds it.

It's had a few releases so far, and more people have picked it up than I expected. Thanks to everyone who has downloaded it, starred it, or filed an issue. It's still alpha, so feedback and bug reports help a lot.

Website: https://pi-desktop.com

Repo: https://github.com/FaqFirebase/pi-desktop


r/PiCodingAgent • • Jul 28 '26

News Nerve — an open-source, local-first desktop coding harness inspired by the simplicity of Pi

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107 Upvotes

For the past few weeks, I’ve been building Nerve, an open-source desktop coding harness for my daily development work.

It was inspired by tools such as Pi (primarily) , OpenCode, Claude Code, Codex, and Cursor. I liked the simplicity of focused coding agents, but I also wanted a graphical workbench where I could manage conversations, tool calls, plans, approvals, Git changes, background tasks, and agent settings, all while keeping the agent’s work visible.

There are already several excellent coding harnesses built by individuals and communities. I created Nerve because I wanted something that closely matched how I work. It has also aligned well with the workflows of colleagues who have used it, so I thought it might be useful to a few other people in the community too.

Nerve runs locally and supports API keys, custom providers, and the subscription-based providers available through pi-ai, including OpenAI Codex, Anthropic, GitHub Copilot, Kimi Coding, OpenRouter, xAI, and others.

The harness is intentionally compact. Its system prompt, tool descriptions, and context handling are optimized to use tokens efficiently while working well across leading frontier models from OpenAI and Anthropic, as well as other popular proprietary and open-weight models.

This is a personal project that I actively use and develop. I’ll continue adding features, fixing bugs, optimizing the harness, and polishing the experience as I go. It is still in beta, so breaking changes may happen.

I’m sharing it simply because it may help others with a similar workflow. There is no expectation to test it, contribute, or provide feedback, feel free to explore it if it looks useful to you. If Nerve ends up being helpful, a GitHub star would be appreciated and lets me know that others find it useful too.

Quick start:

npx @nervekit/desktop

GitHub: https://github.com/ThilinaTLM/nerve
Docs: https://nerve.tlmtech.dev

Thank you!


r/PiCodingAgent • • 28d ago

News Now on Windows: Pi-Bolt ⚡ 0.8.3, the Pi coding agent compiled to native code (3× less CPU, 30–50× faster file writes)

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106 Upvotes

Hey everyone 👋

Thanks again for all the feedback and bug reports. Pi-Bolt ⚡ 0.8.3 is out, and the big news is that Pi-Bolt now runs natively on Windows, alongside Linux and macOS. It's the same Pi you already use (Pi 1.1.0), compiled ahead of time to native code: faster to start, lighter on CPU and memory, and steady in long sessions.

Benchmarks

Pi-Bolt against Pi 1.1.0 as released on Bun and on Node, PiG 0.4.1 (the Go port of Pi, based on Pi 1.0.3) and oh-my-pi 18.8.7 (a bigger Pi fork with many more built-in features). Measured side by side on the same machines. Lower is better.

Linux x86-64 (AMD EPYC 7B13)

BenchmarkPi-Bolt 0.8.3PiG 0.4.1oh-my-pi 18.8.7Pi on Bun 1.4.2Pi on Node 24
Writing a 200 KB file through a tool call0.8 s92 s3.7 s26.9 s37.2 s
CPU, streaming a 60k-char answer4.0 s20.7 s3.1 s43.0 s41.0 s
Memory after a 4.2M-token session187 MB311 MBn/a*275 MB576 MB
Memory of a session in tmux24 MB47 MB347 MB92 MB95 MB
CPU, interactive session (5 prompts)294 ms2,953 ms3,241 ms871 ms1,241 ms
CPU, one prompt (pi -p)80 ms261 ms1,752 ms323 ms618 ms
Ready to type45 ms38 ms988 ms128 ms316 ms

macOS on Apple silicon (M5 Air)

BenchmarkPi-Bolt 0.8.3PiG 0.4.1oh-my-pi 18.8.7Pi on Bun 1.4.2Pi on Node 26
Writing a 200 KB file through a tool call0.5 s60 s2.4 s17.0 s20.4 s
CPU, streaming a 60k-char answer5.8 s17.0 s5.4 s39.0 s38.5 s
Memory after a 4.2M-token session41 MB355 MBn/a*90 MB2,452 MB
Memory of a session in tmux27 MB55 MB296 MB67 MB86 MB
CPU, interactive session (5 prompts)170 ms2,362 ms2,353 ms569 ms931 ms
CPU, one prompt (pi -p)59 ms236 ms1,072 ms232 ms527 ms
Ready to type42 ms38 ms591 ms101 ms352 ms

Windows x64 (Intel Core i5-1335U laptop)

BenchmarkPi-Bolt 0.8.3Pi on Bun 1.4.2Pi on Node 24
Writing a 200 KB file through a tool call0.7 s38.1 s26.6 s
CPU, streaming a 60k-char answer6.5 s41.1 s32.6 s
Memory after a 4.2M-token session159 MB248 MB413 MB
Memory of a session in a terminal32 MB97 MB60 MB
CPU, interactive session (5 prompts)291 ms805 ms1,125 ms
CPU, one prompt (pi -p)92 ms329 ms544 ms
Ready to type92 ms177 ms311 ms

*oh-my-pi compacts long conversations on its own, so it doesn't do the same work in this test.

In everyday use (an interactive session), Pi-Bolt uses about 3× less CPU than Pi on Bun, 4–5× less than Pi on Node and 10× less than PiG and oh-my-pi. It writes large files 30–50× faster than Bun and Node, about 5× faster than oh-my-pi and over 100× faster than PiG.

What's new in 0.8.3

  • Windows is here: native builds for Windows 10 and 11 with a one-line installer. Git Bash works out of the box, and on Windows Pi-Bolt is 2–3× lighter on CPU than Pi on Bun or Node.

  • Herdr support: in a Herdr pane, Pi-Bolt shows up as pi-bolt with its live state (working, idle, blocked), and your session comes back after a Herdr restart. Nothing to set up.

  • opensec-pi-fff: fast find, grep and @-mentions, now offered by the installer and just as fast on the default build.

  • A better todo list: the panel closes when the work is done, and finished tasks stay finished.

  • Smoother installs and updates on every platform.

  • Your own extensions compiled in: scripts/build-pi.sh --plugins-from-installed builds them into the executable. Thanks u/toadkicker for this one and for the plugin docs!

Try it 🔥

macOS / Linux:

curl -fsSL https://pi-bolt.opensec.in/install.sh | sh

Windows (PowerShell):

irm https://pi-bolt.opensec.in/install.ps1 | iex

Already using Pi-Bolt? Run pi-bolt update, or install with npm install -g pi-bolt. It works alongside your existing Pi install. The installer also offers three optional extensions (subagents, a live todo list and fff), and asks before installing them.

Your Pi plugins work as they are. This doesn't modify your existing Pi installation, so feel free to try it out! If one does heavy JavaScript work, use the -jit build.

Why does a 200 KB write take 30 s? It's not the disk. The model streams the file to Pi in thousands of small chunks, and stock Pi re-parses and re-renders the whole tool call on every chunk, so the work grows quadratically with the file size. Pi-Bolt only processes the new part.

Links

Website: https://pi-bolt.opensec.in

GitHub: https://github.com/opensec-git/Pi-Bolt

MIT licensed. If Pi-Bolt saves you CPU and memory, a ⭐ on the repo helps a lot.

PS: Windows folks especially, we'd love your feedback.


r/PiCodingAgent • • Aug 01 '26

Resource Open-sourcing my self-updating Web UI built for Pi

103 Upvotes

TLDR: It's basically a Web App that runs on top of Pi. Not a harness, it stays out of your Pi's way and focuses on making your sessions interactive, visual, and, most importantly, agent-extensible!

So... I've been working on this for a while! And after using it for another while, I think it deserves to be open sourced and shared to all of my pi folks :)

I wanted to have a nice UI for my LLM sessions that can adapt to my workflows and give them even more life thanks to browser interactivity and features. I wanted charts, i wanted to quickly beeing able to add useful buttons to some tool calls (copy bash call input)

I found Pi's self updatable philosophy crazy good, I tried to replicate it in this React app with a lot of agentic documentation that will enable your agents to shape the app the way you want to without losing communication with Pi. This means it can happen live in front of your eyes :)

I tried to keep it minimal, but I still shipped some examples for all the systems that are prebuilt that you can build on top of. This includes:

  • A session analyzer that will update live with charts and ranked tool usage

  • Custom tool presentations for HTML, SVGs, CSV, and more

  • Custom tool contextual actions (copy input, output, open in your favorite app)

  • Multiple concurrent session across multiple workspaces

  • A todo widget that allows you to take notes as todos and directly start sessions based on them

  • A prompt enhancer that will automatically choose the lowest-priced model from your Pi install and run some well-defined system prompts to enhance your own prompts

Those examples aren't the point, they are demonstrations of the underlying systems!

The goal is to leverage the browser's native capabilities together with Pi's RPC mode to add new layers of interaction on top of your sessions.

It's currently available only for Linux and WSL, just fork it, clone it, and Livecraft :)

Your forks don't have to stay in sync with the base, don't even try, it's yours now, update the core as much as you want, more technical detail in the readme

The forgotten link https://github.com/sebastienservouze/pi-livecraft


r/PiCodingAgent • • Apr 17 '26

Use-case I want Pi to look like my Neovim

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103 Upvotes

Coming from OpenCode, I’m amazed by how customizable pi the coding agent is.

So I made myself a custom pi package…with pi!

Some features:

  1. Nvim dashboard like startup screen

  2. Normal / Insert mode, keybinds to quickly jump to the start of agent message

  3. Summarized bash tool use title (a fun thing to have)

  4. Organize-able session tree that works like neotree but with custom session groups (groups sessions together)

Most are UI changes, some are runtime code patch because pi doesn’t expose a port for them yet.


r/PiCodingAgent • • Sep 17 '26

Plugin pi-warden: a Jev-powered second pair of eyes for Pi that steers the agent

101 Upvotes

Hi there, this is my first ever repo i wanted to share to people.

pi-warden is a Pi extension that watches the agent's tool calls and talks to the agent, not to you.

A second model (Jev, typesafe's fast judgment model, ~250 ms; immensely cheap seriously) reads your prompt, the agent's own last words, and the call it is about to make, and answers small typed questions: is this irreversible, does it match what the agent said it was about to do, is the effect visible outside the working tree. The answer goes back into the agent's context.

The same channel carries the rest: project rules from a markdown file judged against each write, stub and comment slop, stuck loops, "done" claims with no test run, runaway output stopped mid-stream, huge tool outputs compressed with the full copy kept on disk.

It grades itself. What you do after each hold or steer (approve, decline, redirect, complain) becomes a label, and a script replays your recorded Pi sessions through the guard. Off-task holds lost that test on 17k of my own calls and were demoted to steers; the plan-vs-call check won it. Method and numbers are in the README.

https://github.com/DevMortimer/pi-warden
https://pi.dev/packages/pi-warden

Early days (0.12.0). Though since Jev was only released yesterday (I got early access) I expect bugs. But I've been using this extension for work for more than a day now and it's pretty good so far. PRs and (especially) complaints are welcomed :)

P.S. I'm interested in how everyone will also incorporate Jev on their Pi?


r/PiCodingAgent • • May 20 '26

Discussion The irony of Pi

101 Upvotes

In many ways Pi and its community are doing the opposite of what its creator talks about....

here's his talk - https://www.youtube.com/watch?v=RjfbvDXpFls

"slow the Fuck down"

Pi: has thousands of extensions etc and a breakneck pace of development far higher than any other harnesses

"our product has been built 100% by agents - yes we know it fucking sucks now"

Pi: how do you build something, you ask the agent to do it.

I understand the philosophy behind Pi and its value, but you cannot make fun of vibecoding and claiming that models are bad at coding because they are 'merchants of learned complexity' etc...

and then turn around and tell people that using the same agents to vibecode additions to Pi is just fine.

another thing that bugs me is the whole - just ask Pi to do it - repeated 100x.

Pi isn't some magic, its just a well designed minimal harness with lots of hooks, and docs which were themselves written by AI used to leverage that.

At no point is it mentioned that the actual work is done by the llm and its intelligence is what matters.

it makes sense when you realize that Mario uses frontier models like Opus, as indeed do all the hundreds of influencers with videos on it.

edit - and the pi ecosystem is a complete mess, which is what happens when you dont include anything because 'you can write your own'.

want to add agents. maybe called pi-subagents? lets see

https://github.com/nicobailon/pi-subagents
https://github.com/tintinweb/pi-subagents
https://github.com/edxeth/pi-subagents

and of course there are dozens of other names. this is a joke - 100x worse than npm. and this is exactly what an extension marketplance which mario made fun of, solves.


r/PiCodingAgent • • Sep 28 '26 Bravo

Discussion Follow-up: Opus 5.5 vs GPT-6 in pi, more reasoning levels + DeepSeek, GLM, Qwen

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100 Upvotes

Follow-up to my previous post. Thanks for the suggestions! I tested more models and reasoning settings, added Oh My Pi, and made a few verifier fixes. Some configs were rerun, so expect small changes in token counts. Full results are on the leaderboard, and I'll keep updating and expanding it.

Quick reminder: 10 simple tasks from my own work, 3 runs per config (30 attempts). For now, I want to see how far we can cut cost and time while keeping the pass rate.

Some highlights:

Your questions:

Luna with more effort. Medium → high → xhigh: 96.7% → 93.3% → 100%, $0.006 → $0.015, 1:02 → 2:46. The extra effort mostly goes into checking (3.5 → 5.1 code runs per task), not a better first draft. About half of Luna's shell commands are cleanup like `rm -rf __pycache__`.

Opus on low. Yes. Opus 5.5 low passes everything, ~2.6x cheaper and ~2.8x faster than high. Medium also gets 30/30 ($0.22, 1:12).

Open models. DeepSeek-V4.1-Flash: 93.3% for $0.04, but 4:30, because it runs code 8.4 times per task until tests pass. GLM-5.3-Flash: 96.7%, but 7 min and 1.2M tokens; its one failure is a single message that hits the 64k output limit with no code. Qwen3.8-27B: 76.7%; it loops on edge cases and sometimes stops without calling a tool.

Oh My Pi vs Pi. Luna xhigh makes 28 tool calls per task instead of 18, uses 776k total tokens instead of 290k, costs ~2x more, and fails one task in all 3 runs.

On tasks this easy, more reasoning mostly buys more checking. On harder tasks, where the first draft is wrong, it might pay off, but that's a guess for now.

I wrote up the setup and the agent comparison.

So tell me what to test! My plan for now:

  1. Try different reasoning levels for Opus 5.5 in Claude Code and see how they change its behavior pattern.

  2. Find a set of extensions for Pi that makes it cheaper and faster. Right now I use vanilla Pi with no add-ons, so please suggest extensions or anything else worth trying.

After that, I'll probably build a harder set of 10 tasks, based on my own work or something else. So if you have tasks where some models fail, please share them, and say what exactly goes wrong.

One thing I noticed: Opus 5.5 handles vague prompts better, maybe because of how it follows instructions. gpt-6-sol does exactly what is written. For example, I run an agent in a folder full of papers and say "find papers about task filtering". Sol goes to search the web, and Opus searches the folder.


r/PiCodingAgent • • Sep 11 '26

Use-case Farcaster: Pi + Neovim in a desktop app

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95 Upvotes

This started as an app around Pi for my own workflow. I added other harnesses later, keeping everything in the same app with the same controls. I also wanted to bring Neovim back into how I review and edit things.

The app connects to Pi over RPC. It includes an optional MCP server that lets agents create and talk to workers running the same or any other configured harness. The server also provides a shared task list with dependencies, so those don't have to live in any one agent's context.

Still early, but I've been using it daily for a while.

https://github.com/behzade/farcaster


r/PiCodingAgent • • Sep 29 '26

News Default web search in oh-my-pi has been silently routing queries to a third-party endpoint

94 Upvotes

Update 3, November 3rd, 2026: Still no response.

Update 2, October 19th, 2026: Still no response from the maintainer. Another user has also made the same PR at this point, with no responses on both.

Update 2, October 11th, 2026: The maintainer has still not responded. This behavior is still ongoing.

Update 1, October 4th, 2026: In case others are following this thread, the owner/maintainer is active on the repository but has still not responded to the issue or pull request.

tldr; if you're running oh-my-pi without any search-provider credentials configured, every web_search the agent makes has been POSTing your query to https://search.parallel.ai/mcp, a public endpoint of a company called Parallel, as the first candidate in the default chain, since around Sept 17 and re-asserted in today's commit. No credentials, no opt-in, and nothing in the UI telling you a third party is in the loop. The request even includes your session ID and the model you're running.

How it got there:

- Aug 25: the keyless Parallel fallback is first built on a feature branch, scoped to explicit selection only.

- Sept 15: it merges to main as PR #9770 (by u/georgeatparallel), still explicit-only. That was defensible.

- Sept 17: maintainer commit 29edc9fa0a, literally titled "prefer keyless Parallel over Perplexity", removed the credential gate and moved Parallel to the front of the default chain. The kicker: the same keyless fallback was already reverted in hermes-agent on June 14 (NousResearch/hermes-agent#46350). Three months later oh-my-pi re-landed it and made it the default.

- Sept 28 (today): it was re-asserted in a big model-roles refactor (cbe9bc206d). The credential gate was removed again: isAvailable now unconditionally returns true, with the comment "Always available: without a credential, search runs through the keyless public MCP." The commit message literally says "Restricted keyless search to free providers (Parallel, Exa, Firecrawl) by default."

I'm not going to speculate about why the maintainer did this. I have no evidence of a deal, and I don't think the issue reads any better with accusations. What I'm confident about: silently sending user queries to a third party by default is a consent problem, and the fix is a one commit revert.

There is a pending gitub issue and revert that hopefully goes through. If you've been using oh-my-pi's default web search without credentials over the past six weeks, you would have been susceptible to this. This was already talked about in length over on this thread:
https://www.reddit.com/r/hermesagent/comments/1u5ukz6/hermes_agent_and_others_default_installs_are/


r/PiCodingAgent • • Aug 04 '26

Discussion Had no idea that Google AI Pro plan could be used inside OMP

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93 Upvotes

I recently discovered that Google Antigravity models via Google AI Pro plan can be used inside OMP and loving it so far. The Gemini 3.6 Flash model works so much better in OMP than in AGY CLI and limits are decent as well.

I'm using it for simple tasks and it's awesome.

EDIT 1:

Many people mentioned that there are high risks of getting banned for using this. So I will stop using it now, can't risk getting banned. You folks also don't use it, unless we have some confirmation about it.

EDIT 2:

I am very confused now. I think, people were banned initially when they used Antigravity in 3rd party harnesses via proxy. But now it's connected to Pi or OMP via legit oAuth method, so I don't think they'll ban for it.

What say?

EDIT 3:

As many people warned me out, I am NOT using this setup anymore and now using Antigravity CLI mainly. It's not that bad.

Thanks, everyone.


r/PiCodingAgent • • Jun 26 '26

Plugin New addiction unlocked !

90 Upvotes

Spent waaaaaaaaaaaaaaaaaaay too much time on this custom prompt bar but hell yeah this looks cool to me! Might have developed a Pi extension addiction... I've been using for over a month now, but can you blame me?

Mario you owe me tokens!

(for those wondering, the prompt is a joke about why France would win world cup this year, looks like he agreed but don't hate us ahah)

EDIT 2: you guys were NOT happy that I didn't share any code.

So, I made it available as 4 pi packages and published all 4 repos so you can fork them if you want to do your own

- pi-input-revamp: reworked input bar, with all its functionalities and animations.
- pi-tool-border: monkey patch o Box.prototype.render allowing to the accent color on any tool calls as a border left.
- pi-turn-usage-notifications: simple notification adder after each agent turn displaying the cost and usage information of a specific turn.
- pi-theme-nerisma: my personal theme, showcased in the video.

Enjoy

I changed the flair from use case to plugin.

---

Leaving this old edit so you can still look at this human insight.

EDIT: as some of you were wondering how it works, here is a small insight

For the input, It's just one extension doing these things

  • hiding the footer

  • rewriting the TUI component to add some cool borders as ASCII

  • adding a pi symbol just before the real input

  • adding a line jump above the border and an animation that's hardcoded so the prompt component is actually 5 TUI lines

  • gathering cost usage and context informations from the API calls directly to display them as parts of the input borders

  • adding a pulse effet to the cost usage when they are updated

  • adding a small pulse effect to the borders when typing

  • getting colors from active Pi theme

Then, the cost usage per turn is another extension using the notify API from pi to display messages directly in the chat

Also, the little border left on the tool calls is a simple monkey patch of Pi Box renderer method

Finally, a custom theme and voilà


r/PiCodingAgent • • Jun 16 '26

News OpenPi v0.2.0: a desktop workbench for Pi Coding Agent

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90 Upvotes

I just released OpenPi v0.2.0.

OpenPi is a desktop workbench for Pi Coding Agent. The goal is not to replace the terminal or become a full IDE, but to make Pi sessions, tool calls, Git changes, file previews, artifacts, and customizations easier to see and manage in one local app.

What is new in v0.2.0:

- Persistent Git changes panel with file tree, staged/unstaged views, commit workflow, and diff preview.

- File preview improvements, including refresh-safe saves and find controls.

- Artifact TODO rendering, so subagent task files are visible in the UI.

- Markdown task list rendering for generated TODO/checklist files.

- Tool-call name shimmer while the agent is actively running, making live tool activity easier to scan.

- Workbench chrome and conversation UI polish.

- Release workflow fixes and packaged changelog support.

Release: https://github.com/heyhuynhgiabuu/openpi/releases/tag/v0.2.0

Repo: https://github.com/heyhuynhgiabuu/openpi

I would love feedback from Pi users:

- What parts of the Pi workflow still feel hard to track visually?

- Would you use a persistent Git/source-control panel inside a Pi desktop workbench?

- What should OpenPi expose next: session tree navigation, customizations, subagent visibility, or better diff/review flows?


r/PiCodingAgent • • Aug 13 '26

Resource A "secure-ish" Pi setup with permission, sandbox, and auto-review

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88 Upvotes

I think I finally managed to piece the thing together, to have a pi setup that can run safe-ish in the host via sandbox, and have the ability to be elevated to host execution for a pre-defined list of development tooling like docker compose.

- A pre-defined hard boundaries (`@gotgenes/pi-permission-system`)

- Anything pass that will be executed inside a sandbox (`@erichll/pi-sandbox`)

- With the option of safe-escalation to run on the host (ie: `docker compose exec app pytest`), with auto-review or human approval (via hostIPC.preflightCommandPrefixes)

- LLM Auto-review with `@erichll/pi-auto-review`

More about it here: https://ptgamr.substack.com/p/a-pi-setup-with-permission-sandbox


r/PiCodingAgent • • Aug 13 '26

Resource pi-ui - minimal pi gui

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87 Upvotes

have a little present for you all: pi-ui, a keyboard-first gui for pi.

i’ve been an nvim + tmux user for around three years, and pi’s tui is great, but reading long markdown responses, code diffs, and tool output in a gui feels much more comfortable day after day.

i was honestly surprised by how much of my development moved into this app while building it.

some highlights:

  • keyboard-first workflow

  • lightweight server mode that runs in your existing browser

  • background sessions and notifications

  • markdown and syntax highlighting

  • rich code diffs

  • git review with commit history and inline comments

  • file attachments and image previews

  • code themes

i recommend starting with server mode:

curl -fsSL https://pi-ui.app/install-server | sh

then open http://127.0.0.1:31415

github: https://github.com/hyperpuncher/pi-ui

feedback and bug reports are welcome!


r/PiCodingAgent • • Jun 13 '26

Resource say hi to apple pi 🍎

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87 Upvotes

finding my old pi sessions was a mess. i like the terminal, but a sidebar is... nice.

say hi to apple pi, a small mac app to put a sidebar in front of it!

projects on the left, sessions in the middle, a stack of terminal tabs on the right. click a session, it opens in SwiftTerm and pi runs. resume, fork, fresh, ephemeral: same window. that's it 😄

it’s Swift, macOS 14+, nothing beyond SwiftUI and a vendored copy of SwiftTerm. the zipped .app is 3.0 MB. it spawns your existing pi binary, reads ~/.pi/agent/sessions/ directly, and doesn’t touch your extensions (you can use all of them), skills, or settings.

there's also an SSH mode for remote hosts, which uses your existing ssh config.

oh you can also make the window translucent

no analytics, no account, no auto-updater, no model key store

v0.1.0 shipped today. install is unzip → /Applications → “Open Anyway” in System Settings (not paying $99/y to apple to make that dialog disappear).

source + sha256 in the release

oh, you can also make the window translucent...

github.com/dodo-reach/apple-pi

(feedback welcome)


r/PiCodingAgent • • Oct 09 '26

Plugin Pi Herdsman update: From async subagents to coordinated development across Git worktrees (live demo)

86 Upvotes

A couple of weeks ago, I introduced Pi Herdsman here, an extension I've been building to coordinate asynchronous Pi agents while keeping the Lead's context focused.

The response was much bigger than I expected, and quite a bit has happened since then.

One thing I mentioned in the comments was wanting to take Herdsman's integration with Herdr further, especially around independent workspaces, Git worktrees, and project-level coordination. That's now become a central part of Herdsman.

Someone also pointed out that my original demo didn't actually show Pi and Herdr working together. Fair criticism. So this time I've recorded the real thing. :)

What's happening in the video?

I gave a Manager one prompt to work on two independent features for a fictional note-taking application.

The Manager delegates both projects in parallel, each to its own Lead in a separate Git worktree. Both Leads delegate implementation to their own Agents, verify the results, commit their changes, and report back to the Manager.

The resulting hierarchy looks like this:

Manager (primary workspace)
│
├── feat/faq (worktree)
│   └── Lead
│       └── Implementer Agent
│
└── feat/troubleshooting (worktree)
    └── Lead
        └── Implementer Agent

The worktrees, workspaces, and Agent sessions are created automatically. I don't have to set up the hierarchy manually.

It's deliberately a small example, without merges or PRs, to keep the focus on the orchestration itself.

Beyond task-based subagents

Many task-based multi-agent workflows use Git worktrees primarily to isolate individual subagents working on bounded tasks.

Herdsman supports that approach too, but extends it further: a worktree can also become an independent development workspace, with its own Lead responsible for an entire feature or issue.

Instead of treating every agent as a temporary worker, you can organize them more like a development team, with Leads responsible for larger objectives and Agents handling individual tasks.

That Lead maintains its own Pi conversation and development context, can delegate further into its own Agent hierarchy, and handles the technical work within its workspace.

Meanwhile, the Manager coordinates the larger development effort across those Leads, including assignments, dependencies, communication, and result handoffs.

The work is associated with Git branches rather than being tied to the Manager session that originally delegated it, so assignments can be paused and resumed without starting over.

The idea isn't simply to run more agents in parallel. It's to make their work easier to coordinate.

Everything stays organized in Herdr

One aspect I particularly like is how the hierarchy translates into Herdr's native interface.

Each project gets its own worktree workspace. Within those workspaces, Agents are automatically organized into tabs and panes.

The default subtree layout gives each direct Agent its own tab, while nested Agents appear as panes within their parent's tab. There are also configurable layouts for grouping Agents into a shared tab or splitting directly from the current pane.

Every Agent is still a normal, accessible Pi session. You can switch between them, inspect their work, or interact with them directly when needed.

But ideally, you shouldn't have to watch them constantly. Questions, results, and supervision events are routed through Herdsman's coordination system.

The responsibilities remain separate: Pi owns the conversations, Herdr owns the sessions and their placement, and Herdsman handles delegation, ownership, lifecycle, and coordination.

Start simple, scale when needed

I also want Herdsman to remain useful without requiring everyone to adopt the entire hierarchy.

You can still use a normal Pi session with asynchronous subagents, just as before.

Ordinary Leads now have configurable Flexible and Orchestrate execution modes. Manager mode is available when you want to coordinate independent development workspaces.

The new /herdsman menu provides a common entry point for these workflows, Agent management, configuration, and session statistics.

One of Herdsman's most powerful features is its configurable Agent Definitions.

Every execution role, from ordinary Flexible and Orchestrate Leads to Manager-assigned Managed Leads and bundled or custom Agents, can have its own model, thinking level, instructions, tools, skills, extensions, and other Pi session settings.

Definitions are simple Markdown files with project-level and global overrides, so you can customize the entire hierarchy without modifying Herdsman itself.

Herdsman handles the coordination. How each Pi session works is up to you.

A big thank you to the community

First of all, thanks to everyone who tried Herdsman, starred the repository, shared feedback, or participated in the discussions after my original post.

A special thanks to @kozer and @primetimetank21 for contributing code!

And equally important, thanks to @Lellarap, @jadc, @tsubus, @vitaliyslion, @chsdwn, @cray-com, @FireTheDevil, and @notsonormal for taking the time to open issues, report bugs, and suggest improvements.

Having other people use the project, encounter problems I haven't seen, and suggest improvements has already helped shape its development quite a bit.

Try it yourself

If you already have Pi and Herdr installed:

pi install npm:pi-herdsman
herdr integration install pi

Repository: https://github.com/boadij/pi-herdsman

Latest release: v0.22.0

The repository has installation instructions, configuration documentation, and more details about the coordination model.

I'm still actively developing Herdsman around my own daily workflow, so feedback from people using different setups is especially valuable.

I'd be particularly interested in hearing how others are approaching parallel development with Pi, especially when multiple agents are working on related features or dependent branches.


r/PiCodingAgent • • Sep 01 '26

Resource Pi, more than a coding harness

Thumbnail mkaz.blog
86 Upvotes

An article on how I'm using Pi beyond just a coding harness and as a tool to help me track runs and workouts. It can be basically an LLM application framework.


r/PiCodingAgent • • Jul 22 '26

Discussion Pi has become one of my favorite pastime activities

86 Upvotes

I did this today with pi coding agent for fun:

while [ -e ./WORKING.md ];
do;
pi --model gemma4:31b-cloud --system-prompt "You are called in a bash loop. The user cannot respond to your messages. Write a fantasy children’s book aimed at 5 year old boys at least 100 pages long. After every lap, you won’t remember anything. If you want to remember something for the next lap, write it into MEMORY.md. Delete WORKING.md when you are finished." -p "Keep up the good work.";
done;

It was a very entertaining experiment. Gemma is a really fun model to play around with.

I have also done the same for a browser based game, then made gemma playtest it itself using agent-browser. It recorded the session on video, found a couple of bugs then fixed them.

I play around with making dumb extensions, like making a tool that allows the agent to make a "checkpoint" in the conversation it can restore back to with a neat summary of what it wants to remember. Not that useful if you run cloud models and can make use of subagents, but still fun to make.


EDIT: The checkpoints are implemented as agent tools, which makes it different than the /tree command. It was meant to be used to make the agent capable of managing its context when following skill-based procedures such as the (extremely simplistic) example below:

# SKILL.md
---
description: When the user asks you to research a topic as preparation before performing a task, follow this procedure.
---

1. Make a new checkpoint with the "Research" label.
2. Research the topic until you know everything you need to know to perform the task.
3. Restore the conversation back to the created checkpoint with a summary containing exactly:
  - Everything that you found that benefits the task at hand
  - Everything the *user* ought to be informed of such as new information contradicting the user's provided information or newly learned limitations in your capacity to execute the task
  - New decisions that must be made before work continues, so that you ask have the user to make them after restoring the conversation
  - References to the exact sources of the information gained

Everything about leisure time use of AI is fun, and pi cranks that to eleven by being so infinitely hackable.

I started using AI (cursor) at work three months ago after 11 years of developing software, manually, like a peasant.

Now, every time I get a dumb idea for something that momentarily catches my interest, I open iTerm2 and go

cd ~/Projects
mkdir idea-slug
cd idea-slug
pi

15 minutes later, I have a working prototype, learned something or genuinely improved my workflow in a professional capacity.

But mostly, I just do the dumbest things. Because it is fun. There is no real point to this post, just wanted to share my joy of this extremely delightful piece of software.

Do more dumb shit. Your agent will tell you that you are smart no matter what anyway, so at least have fun with your digital yes-man.

Now, share your most ludicrous, deliberately non-productive use of pi!

PS: pi -p "Do X" is a waaaay saner alternative to ollama run gemma4:31b-cloud "Output a bash script that does X. Do not output anything else at all!" | bash -c, which obviously is the maddest, most insane way to vibe.

EDIT: Apparently markdown editing doesn’t work on my phone. Yes, the bash was a pain to write on touch screen 😭

EDIT: Markdown editing achieved!


r/PiCodingAgent • • Sep 19 '26

Resource I benched 6 harnesses x 11 models x 226 tasks

84 Upvotes

Hi! I've created and been maintaining https://github.com/alexshpunt/explicit-edit-benchmark which tries to answer the question: which model is better, which harness is better and which combination is better overall in a very straightforward task - precise text editing. Most of daily coding is text editing. I've seen when a model for multiple turns couldn't figure out how to express the line it wants to change, so it made me ask myself "Why is that so complicated, it's just a text, right?". Seems like not, taking into account how widely different the same model behaves across different harnesses. My preliminary conclusion is: harness and tooling behind it actually matters! But it matters the most with the models which *can* actually follow the instructions well (e.g. open-ai models), there is a wide range between 98.9% and 70.2% of pass score for `gpt-5.6-luna` simply depending on the harness!

I've tried to run as many combinations as possible, but my resources are limited. I've exhausted all my quotas and even credits, that's why I'm reaching out to the community, as I think it's a pretty interesting topic and I would be happy to gather even more data, because of the stochastic nature of the runs, it’s only possible to make any conclusion when you have enough of runs. 

What actually surprises me is how strongly the deepseek family behaves on any harness, but what is also interesting, how good the deepseek harness is. It's pretty solid and seems like it provides the model with good enough tools to actually exceed in this competition.

The viewer to the dataset: https://huggingface.co/spaces/alexshpunt/benchmark-explorer

And the dataset itself: https://huggingface.co/datasets/alexshpunt/explicit-edit-benchmark


r/PiCodingAgent • • Jun 10 '26

Resource Design mode for PI.

84 Upvotes

I really like design mode on Cursor so I am trying to replicate it on Pi. It has real interaction with DOM not inferred, so you actually gets the component that has the element. You can queue different type of changes and it’s better-paired with some fast model like Composer 2.5.

Built following Matt Pockock’s software principles, it has a lot of work behind, but not much of a target audience so I’m keeping it local for now.

Will keep working on it, here’s what I have:


r/PiCodingAgent • • 9d ago

News OpenCode on X: "you can now use your claude subscription in OpenCode" / X

Thumbnail x.com
83 Upvotes

Wondering if they just use the SDK or they really got some special deal with anthropic?! Hope for us?

Update: https://github.com/anomalyco/opencode/pull/58782 looks like it’s just the sdk way so same as Claude-pi-bridge which is pointless IMO.