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?
So Pi is a lot of fun. I’ve been working on Volt, a fork of Pi, mostly out of my frustrations with remote development. I expanded out the existing RPC and built a mobile app around it.
It kind of just gets with how you creative you want to be about it.
You use it, then something bugs you, then you find an extension that solves the problem, or tell an agent to fix it for you by making your own extension.
It's kinda a tinkerer hobby IMO. I like the freedom, but at the end of the day, it's still just a harness.
I run it with a single extension to give it web search access, and then I have a few skills for reviewing and planning. You really don't need that much IMO
If you can't find a use for it, then don't use it. So easy. 99% of AI related things are mostly hype and totally useless. Adult childrin having their shiny new gadgets make them feel 14 year old again and again.
Oh My Pi comes preloaded with most stuff you need, so there's not much need to add extensions. <a href="https://github.com/can1357/oh-my-pi" rel="nofollow">https://github.com/can1357/oh-my-pi
IndyDevDan videos are great for learning the basics <a href="https://youtu.be/f8cfH5XX-XU?si=gm-trlU7RTG4wVjJ" rel="nofollow">https://youtu.be/f8cfH5XX-XU?si=gm-trlU7RTG4wVjJ
It works ok and good by default. You start using it as if you'd Claude or Codex, the when you find yourself missing a feature, you get an extension for it or you ask an agent to make it.
For example, I started using it, wanted a plan mode, downloaded an extension for it. Wanted to be able to analyze token usage for turn in a session, I had an agent create an extension for that. Then I wanted a custom status bar, so I had an agent implement an extension for that.
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 I'd never go back.
Personally I use gh copilot in vscode and make new worktrees when I want parallel agents that are both going to write code.
For research, planning, figuring out bugs, etc I usually don’t bother creating the worktree until I’ve decided on the implementation.
I’m sure there’s better workflows and software, but all I’ve got for work is gh copilot and Claude enterprise. I like copilot better than Claude for the most part.
onorca.dev. I used herdr before now Orca has fully replaced it. (I'm not affilianted with Orca in any way except I use it every day).
Orca also supports separate hosts.
My setup
Orca running in my Mac. Orca running in my home proxmox lxc (orcabox).
I have few different projects, Rails, PHP, etc. In Orca, I open these projects and point it to my local folder as well as the folder remotely.
I usually start a codex or claude session on the remote host, close my mac, even restart Orca desktop on mac, but when I start Orca, I can watch the Orca on my remote host working through.
It's similar to Claude remote session, but just easier to manage, easier to create worktree, easier to navigate, open multiple tabs etc.
you can just roll your own, this is probably the most popular side project of the past year, I crafted my own version within a day or so this past week, with corny visual assets as well since its just for me. Kinda rolled my workflows into it so it fits how i work with plans and how i avoid compaction in favor of handoffs or just plan docs that constrain each session to x amount of tokens each session.
Tossed all my weekly usage for each provider at the top with their 5hour windows and such. its been great so far.
Yeah I also created my own TUI one and only took a couple days. Using it less now though because the models have gotten pretty good at spinning up their own agents.
The important thing is to use one of the GUI agent multiplexers, they're mostly doing the same kind of thing. IMHO it's very important to have the official claude and codex harnesses (not just models).
I usually recommend Conductor to most people. Personally, I use the one I built, but it's got a few ergonomic issues for most people which I still need to fix.
Paseo allows you to start a daemon from command line, thereby passing your ENV credentials to the daemon from, say, your 1Password-based env. Then both local Mac GUI and their native iPhone app (through Tailscale) can connect to this daemon. This is the most ergonomic local and remote setup where I can start a session on my Mac and continue on my phone or vice versa, with any agent: Pi, Claude, Codex, OMP, all natively supported.
No affiliation, just arrived at Paseo after a bunch of research.
I've eventually settled on a CLI agent multiplexer that essentially run in the background while the frontend is a GUI gateway agent to that backend system with a goal middle layer so I no longer need to interject directly into the prompts and forces the CC and Codexes to communicate to me in a structured format relevant to my purpose.
If you like the terminal I'm building <a href="https://alcubi.ai/delegator/" rel="nofollow">https://alcubi.ai/delegator/ It's terminal based and I've taken a different approach to avoid context overload of switching tabs. Agents run in the background and you review the work when it's ready.
There's something about this take that... irks me. A little bit more every time I hear it, and I've been hearing it a lot. I dislike the implication that anyone who takes more care with their setup than downloading an exe from a website and double clicking it is some kind of chump. They could be prompting the next ticket instead!
Even if taking pride in your tools was a productivity killer (I have my doubts), maybe there's mental value to be gained.
You're inferring things I did not actually imply.
In Oct 2026, if you're optimizing for productivity, then yes, you probably should just use both Claude and Codex and not mess around with alternatives.
If you care about other things, then have fun, no one is stopping you. Just don't pretend you're doing it because you take more "pride" or "care" in your tools. That's just silly.
You're inferring things I did not actually imply.
If you're optimizing for productivity, then yes, you probably should just use both Claude and Codex in a GUI agent multiplexer. If you care about other things, then have fun, no one is stopping you.
It's not an either/or. Orca is a GUI agent multiplexer that works with dozens of harnesses, including Pi. The advantage with Pi is that you can vibe code any kind of extension you want. I like to see various stats (tps, ttft, etc) on each turn, and there's an extension for that, but it doesn't show wall clock time for the turn. Ok, pull down the extension and tweak it to add that. It's great.
I believe this is the popular "batteries included" kit: <a href="https://github.com/can1357/oh-my-pi" rel="nofollow">https://github.com/can1357/oh-my-pi
I know that's a way omp is often introduced but I don't think it's fair for either omp or pi - after lately switching more to omp I'd say by this point they're almost more different than Pi and Codex. And I like them both.
Yeah I just gave it a run and it starts off burning 6% of my tokens on start.
Pi sits at 0%.
I'm so use to the command keys in Pi that having to type something out in OMP slows me down. I'll stick with Pi, I've built it to my needs and having WSL finally working. I still have to run 2 CLIs, one for LLama.ccp and the other for Pi, not sure if this is normal.
OMP provides a significant amount of structure to the work. That costs some tokens in terms of the system prompt. When I use these systems, I balance the return of the extra guidance in the system prompt with the cost of the context. You've talked about how much context it takes, but you haven't talked about any difference in behavior.
omp offers some nice tools, like /shake, to manage context efficiently and offset some of that consumption.
Not sure about your point with command keys. OMP has all kinds of shortcuts and is highly configurable. It seems very unlikely that you cannot achieve what you're looking for in OMP in terms of shortcuts. Specifics would be immensely helpful here.
And yeah, you'll need to run your inference engine separately from your harness, for the same reason the web server and the web browser are different applications.
That the "batteries included" bit, but it's not "burning tokens" in the sense that using Pi with the same batteries would (of course) use just as many. I can strongly recommend omp.sh if you just want to be up and running without hassle and a far better (for me) developer experience.
Yeah, saying it kills the minimalist bit misses the point of omp being a separate project. It took a minimalist-base of pi and added tools that make it usable out of the box. Hence batteries.
One example here is that it added MCP extensions to make the harness usable with MCP servers long before Pi figured out that that was the right move. A lot can be said about development of MCP over that timeframe, but I appreciated the bias towards adoption, since progress is driven by empirical experimentation rather than theory in this domain right now.
I've long championed assembling developer tools yourself from scratch and I've been an advocate of vanilla Emacs and customizing it yourself as an ideal developer experience (I realize this opinion is controversial). But OMP is essentially the VSCode to pi's Emacs.
I ended up choosing omp as my daily driver, mostly because I see the velocity of change in AI development being far too fast for me to make a worthwhile investment into customizing the environment myself, since that investment will have a relatively short half-life. With Linux, which I learned more than 30 years ago and still believe to be a fantastic investment, I can largely use the same knowledge I gained then to administer systems today. I fear that much investment in the specific tools that I add to my pi harness will expire before 2027. So I'm sort of drafting OMP until things settle down.
I am wondering what use people get out of this. What I like about pi is that, using proprietary harnesses to begin with, I already somewhat know what kind of features I use and features I wish I could use. Asking pi to self modify itself (with a smart enough model) is a one time cost for a fully vetted feature that I personally approve. Do users of OMP find all of its additions useful?
Yeah, Advisor and "time-travelling rules" (TTSR) work great (they're injecting corrective prompts automatically either via another critic LLM or a bunch of regex rules, respectively)
It automates a lot of the babysitting of agents, and lets me use a couple of smaller models with safeguards instead of burning tokens on a galaxy brain just because it listens to instructions in AGENTS.md.
It’s the same kind of people that would use omz, they probably have no idea what 90% of the batteries are or do. But it sure makes them feel smart and cool.
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
qwen3.5 4b and 9b have both been surprisingly good for small tasks. a pattern I've been using is orchestrating pi agents with a script (that you can write using a frontier model) for common tasks. one script i use a lot is organizing photos from my photography shoots.
What does a "script" mean in this context? Like a Python script that runs a series of agents with small tasks? I'm still getting used to doing things with AI, this is all very new to me.
I have more beefcake machines and Qwen 4.6 36B has been awesome for coding. Its fast for a local model, seems to get a lot right most of the time, just its slower than OpenAI/Claude/Cloud Hosted stuff since I dont have a 24GB+ GPU (I have Strix Halo and a 12GB GPU)
> 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.
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
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).
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)_/¯
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. \
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.
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.
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.
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.
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 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
Codex generally lets you use the subscription with 3rd party agents / harnesses.
ON the PI 1.0 you can directly use the openAI log in to hook up your account, so it should be pretty straight forward. I haven't tried myself yet.
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 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'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'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].
The light weight prompt and simple harness design are a lot of fun. I don't personally mind Claude Code, and I think it Claude Code is well designed for the problem domain, but Pi is a lot of fun to hack with.
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
I use PI WEB (<a href="https://pi-web.dev" rel="nofollow">https://pi-web.dev, there's more than one with that name) to orchestrate remotely. Pi let's 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.
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 have eight or nine custom extensions at varying levels of maturity, some nearing the point where sharing them becomes useful.
Because of Pi I modified my terminal (Alacritty) to support the Kitty image protocol (it already spoke sixel; Pi understandably uses the superior Kitty protocol).
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.
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.
Everything is stored locally (expect cloud runs) in ~/.codex
It lists down everything: conversations, skills, prompt plugins, mcp, conversation history.
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 use Pi because I fundamentally believe that inference providers are not the correct providers of harnesses. Their incentives are not aligned, and inevitably Claude and codex will continue trying to lock you in to get your inference spend.
A lot of us aren't actually using enough tokens to reach the value add of a $20USD/month subscription versus just paying for the API. Without even mentioning the chinese competitors, you can get a lot of tokens for $10 of ChatGPT Luna, which is more than capable of solving the kinds of problems I have at home (where I use hermes harness).
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.
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: <a href="https://forge.l3x.in/alex/pi-shared" rel="nofollow">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: <a href="https://a.l3x.in/ai" rel="nofollow">https://a.l3x.in/ai
I also maintain a couple of other Pi-related projects:
I built <a href="https://rcarmo.github.io/projects/piclaw" rel="nofollow">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.
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.
I'm using Pi with Herdr as well right now. It's been quite nice. (I use the organization similar to projects for the Claude / Codex GUIs).
Herdr is OK - but the actual interface / layout is nice. I previously would have like 6 terminals open and would lose track of which was which. I'm not super into the subagent workflows, but it's been helpful a time or two.
The only reason Herdr is just OK is because using agents to collaborate will sometimes just hijack my prompt input field. Maybe I'm using it incorrectly but I would have thought they might have a more elegant solution than that.
I don't really understand the criteria for when something is 'proven' to the Pi team. Jev and the like took off less than a month ago, but MCP has been growing for nearly 2 years, and it only gets support now?
Pi felt nice when I used it, and I do value keeping things minimal, but I just find the criteria very uneven.
A year later, some things have changed: <a href="https://earendil.com/posts/you-said-no-mcp/" rel="nofollow">https://earendil.com/posts/you-said-no-mcp/
Armin from Earendil here. I think the question is fair, and quite frankly the answer is pretty disappointing: we look at what the models are doing. They are trained on their respective harnesses and we're not here to fight their behavior.
Codex in particular is using responses lite internally and relies on codemode for parallel tool calling. So codemode was a given.
Jev on the other hand is new but it's not the first type of model we had troubles with supporting in Pi and we looked at how to make that make sense. The internal pi-ai SDK supports image generation and classifier models, but without building an extension it was never possible for you to utilize it.
So there was a while functionality of Pi that few people used, because there were no obvious ways to hook it up with the coding agent. Codemode also allows us to close that gap.
And once you have codemode, modern MCP can work quite well if the servers cooperate.
Classification models have been around for literally almost a century at this point. I think it's safe to say they are a proven technology.
The only thing that makes Jev and the likes particularly interesting is that it is a general purpose classifier. In the past, classification tasks meant training a new model to solve your problem. Now you can just use an off the shelf general purpose model and hit the ground running.
It is in that sense not integrated with the coding agent. It's just that some things cannot be done with bash alone, at least not as trivially. So if you were asking Pi to utilize Jev, it would not really have the right tools available to make sense of it, even though pi-ai, the underlying library, can make requests to it.
Codemode as a mechanism can expose non LLM functionality to the coding agent. In that sense, Pi does not have a tool for Jev or other classifiers. It just now makes it easier for the agent to utilize it in the same way as it's otherwise quite creative in using bash.
>it would not really have the right tools available
The point of Pi is that the user can tell the agent to improve itself and give it the tools it does need. The minimalism comes from the user creating what they need instead of the maintainers trying to support everything for the users.
With Pi the agent edits agent itself. That's one of the reasons it's written in typescript, to make such iteration fast. Going even lower, into the language runtime or operating system shouldn't be necessary but technically also possible.
> The point of Pi is that the user can tell the agent to improve itself and give it the tools it does need.
The point of Pi is to be minimal but also follow what the models need. We were pretty outspoken that models need code execution, and that's why Pi to this day has a very small set of tools available. However as more and more training with these models abstracts even over toolcalls themselves with code mode and similar things, it requires changes to Pi.
Mario and I talked about this last week if you want to know our thinking: <a href="https://x.com/pidotdev/status/2104510506627121451" rel="nofollow">https://x.com/pidotdev/status/2104510506627121451
And yes, that's why there is no Jev tool in Pi either.
Well, according to claude and Jevbench, Qwen 3.6 35b with ninfer on a RTX 5090@480W is like 3-5 time slower but 10%-15% better performance on the public set.
Latency against what and which hardware? I don't really get jev...
Look I can convince my boss to pay for jev, but I won't convince him to run our prod stuff on a rented vast.ai 5090. And the pricing wouldn't be worth it. If you have ideas I would be glad to hear them
If you want something even lighter than Jev to compare against, there's also gutsy (<a href="https://github.com/kouhxp/gutsy" rel="nofollow">https://github.com/kouhxp/gutsy) runs on CPU
I agree. I don't necessarily "trust" Anthropic and OpenAI when it comes to CC/Codex respectively, but I respect that they have immense internal resources and telemetry to be able to understand what features move the needle and nudge traces in the right direction. I don't understand how non-labs judge feature inclusion? Just vibes?
This is hitting at the right time. Codex is already in the enshitification phase. They just broke their CLI version with some new thing that no one likes.
You should strongly consider changing your name! I genuinely thought that Pi had been acquired by Anduril when I first read this blog post. I'm sure many people will make the same mistake.
Pi is really good. I use it for a majority of my work.
I also like Autolith. The freedom of having a lisp machine is, to me, much more enjoyable than trying to maintain Typescript. But I'm not a typescript guy.
I do largely stick with Pi because it's very bulletproofed
Woah, this is my first time hearing about Autolith. Definitely looks cool, I might have to play around with it. How do you find models do with Lisp? I have had some trouble with my models getting tripped up pairing parenthesis in my GNU Guix configuration.
I use the open weight models and they kind of suck lol. I have a lot of paren helpers. I think Autolith ships with one also. The boys in the Autolith zulip say that Openai and Anthropic models are all totally fine with parens. Come say hi in the chat
I found oh-my-pi with Paseo to be my personal sweet spot. Checks all of the boxes I want and is the most consistent set of AI tools I've used thus far.
I tried Pi a while ago and found it a bit tough to use, OpenCode was pretty simple, but oh-my-pi is really head and shoulders above the two others. Really great.
A major aspect is that it automated out-of-the-box a pattern I naturally would do of writing a spec just before the context window would fill and then compacting and continuing.
Now I just write a prompt and OMP just hammers away at it. There might very well be some OpenCode plugin for this but it just works out of the box with OMP.
I had a really bad experience using OpenCode with Ox Alpha (when it was a stealth model on openrouter), with the model making countless mistakes. Then I tried omp with the same model and it was a million times better. I haven't looked back.
omp is feature rich, and it's very actively developed. I don't have the time or interest to pick and choose among the thousands of pi extensions, so the fact that omp already has a lot of useful things built it is a good match for me.
Subagents in OpenCode suck. They're blank-slate black boxes that block execution.
OMP spawns agents asynchronously, letting the main agent check on them periodically and even chat back and forth with the subagents to coordinate dynamically instead of losing control after initial prompt (it's also very amusing, like watching Sims play office).
OMP also has /tan tangential prompt which spawns subagents that reuse entire conversation prefix (cached), so you don't waste tokens on sending them a recap of the situation and them re-discovering the codebase themselves. OpenCode kinda does it with fork + switch of sessions, but a command inside one session is quicker.
How do you use omp with subagents and not burn through credits? I tried using orchestrate and it drained my wallet… I didn’t know about /tan though, that is sick
I mainly use Paseo for the daemon features. I run it in a linux VM in my homelab and spawn all of my agent sessions on it. Exposed over Tailscale so I can connect to it from my desktop, laptop, and mobile phone and continue like nothing happened. A really great self-hosting experience.
if you're using herdr/tmux/zellij you could give <a href="https://colliepwa.dev" rel="nofollow">https://colliepwa.dev a try, its a mobile interface i built to interact with agents on the go.
I know this is going to get downvoted but what drives people to use javascript of all languages to build these fundamental pieces of tooling? We have so many better options, especially now since humans aren’t writing most of the code. It’s hard to take seriously anyone that wants to make a primarily CLI tool with heavy interactivity and parallelism requirements and decides to use a joke language that happened to luck its way into prominence because of web browsers.
What would be a better language? Most of the harness apps will be spending most of their time waiting for the models response and tool calling rather than running their code.
Languages with less opensource footprint or too verbose are at the losing side in a llm-driven world.
> most of their time waiting for the models response and tool calling rather than running their code.
You’d think that! Yet claude-code spends a very surprising amount of CPU just doing text layout work and other mysterious things, likely due to their decision to use React to build a TUI for some reason.
You either need to rebuild the harness every time you want to make a change, or a lot of deliberate effort is required to maintain an API surface for extensions, distinct from internal implementations, or you can embed an interpreter like Lua, Python, or... JavaScript. Or you could instead go the Pi route and use an interpreted language, and just load extensions into the interpreter, alongside the program itself. When one of the main goals is extensibility, the latter seems like the obvious choice.
I feel like people have forgot how extensions used to work long time ago with compiled languages. Extensions can be just dynamically loaded, (e.g. DLL from Windows world, .so from Linux). There is no need to compile the whole harness. This is also possible when using Rust, but people are just lazy.
And yes, API must be maintained for compatibility, but that is needed anyway.
Pi is extensible, and to iterate new extensions, install them, create your own, even if the agents needs to, it is much faster and easier to manage that than a compiled language I would suppose. Most of the time it's really the waiting time than anything else. If any, the "resource intensive" parts of the app could be turned into low-level extensions such as writing or reading files, maybe, but the main part of the app makes total sense. The language and ecosystem is fairly accessible as well, which serves as a further argument. Interesting choice of words when it comes to calling it "joke language" really.
I wouldn't go as far as calling it a joke language (in some ways, it's incredible), but I did come here wondering if other people felt this way. The language choice has always confused me.
On the other hand, I don't think there's anything Pi does that another language would do noticeably better from a user's perspective. Any performance complaints I have using Pi come from twiddling my thumbs waiting for Sam Altman's servers to bestow tokens upon me.
At any rate, they'll probably have Opus 6.5 and GPT-7 Galactica rewrite it in rust in a couple months...
Which I believe is what the developer was looking to do. I personally enjoy it being JavaScript. I've had it redo some functions on the fly which to me is perfect.
TS probably has the most expressive type system of any language that I have used, and you can develop at lightning speed without fighting the borrow checker or anything else. The ability to share the exact same code across the front and back end, and encode API contracts in the type system, is a superpower for webapps built with node.
Whether an LLM writes the code or not is besides the point. What matters is that the code should be testable, and understandable. TS wins on both counts, like most sane alternatives.
I personally do not program using any language that does not have the ability to specify types.
Fair enough, I accept your opinion. Out of curiosity, which language do you think would have been better for the web? Visual Basic, TCL, and Python were the other main contenders in the mid '90s. Would you rather be working with one of those nearly every day? If not one of those, then what do you think would be best?
I like that Pi is holding the line on minimalism instead of absorbing every new trend. Curious how Pi Durable differs from existing durable-execution setups for agents
I've been full time building on pi since January and its been incredible. I'm not sure what they did to make it so easy to vibe code against but agents really just "get it".
Can you explain your workflow a bit please? Do any of these tools work with Claude/Codex subscriptions or are they API only?
I actually built my own tool that maintains a work graph (DAG-like) with task leases. It allows me to copy and paste pre-written prompts into Claude Code, Codex, or OpenCode and all the agents self-coordinate through MCP calls.
I built this after trying hermes and Openclaw but not liking the lack of human-in-the-loop judgement. So I'm wondering if I should keep refining my tool, or evaluate something like pi?
Why full screen mode by default? That seems to go against the minimalist theme. I could never get acceptable inertial scrolling behaviour dialled in with other full screen implementations I tried (claude, codex, opencode).
Full screen hides distractions from other applications. Seems reasonable as something minimal.
Minimalism is a difficult subject. In art, minimalists tried to strive for something that is universally minimal. But if you look in nature for straight lines or perfect circles, you end up disappointed. Turns out minimalism found things that were minimal with respect to humans.
You seem to misunderstand what full screen mode is. It doesn't just make the terminal fullscreen, it causes pi to maintain its own scrollback buffer and a UI around it, rather than letting the terminal emulator handle scrolling (ie, letting the session context actually live in the terminal history)
Sigh, looks like Pi's days as a nice minimal agent TUI are numbered. I guess no third-party offering can fight that entropy for long and I'll just have to polish up one of my toy projects
I've read this a bunch of times around socials now these past days and I'd really like to understand what exactly indicates that the minimal agent TUI days are numbered for Pi?
I did not read this when I added support for AGENTS.md, skills, llama.cpp, extensions, alt TUI mode, mid-convo system messages and tool set changes to preserve KV cache, image model support, and everything else I added since November last year.
Codemode and MCP support are the latest additions. We follow what the models are trained on. E.g. the GPT family of models is actually trained on codemode for parallel tool calls now. The MCP spec has gotten a major update recently that makes it much less bad than it used to be in the past 24 months. Combined with codemode, it is now passable, so it got added to pi.
All of these features are still entirely optional and the only thing I could think of that could be considered "bloat" is the additional few megabytes for the QuickJS WASM blob.
So, I mean this in earenst and absolutely not combative: could you explain what exactly flips the switch between "pi is minimal" and "pi is not minimal"?
Fullscreen mode as the default is a big one, I prefer my agent harness to be a CLI rather than a TUI and in fact my personal one doesn't even try to wrap text. Pure CLI output model.
That said I also dislike many of those other changes and would prefer a hypothetical version of Pi which didn't have them, so this is in some sense just me looking up at the sound of a v1.0 release and realizing "oh hey, I don't really like the direction this has been trending for a while"
Multiple answers. Windows Terminal users constantly had problems because WT is ... not great. Fullscreen mode fixes that. This also applies to some other lesser used terminals.
I wanted the out of the box experience to be smoother for more people, so made it the default. Scrollback mode will stay though for users who prefer it.
> and would prefer a hypothetical version of Pi which didn't have them
If only there was some way to... ah no time to be snarky. It's open source and MIT licensed and you're in a thread discussing AI coding agents.
Sounds to me like things people say just to have something to say. True, it is good to listen to feedback but feedback without evidence is only going to waste your time.
Thanks for all your hard work and keep going in the direction that makes sense to you!
Well, I'm happy. Thanks for the new harness, ripping out the guts of piclaw to use it, and also flipped a few other small tools to pi-durable, which is nicely streamlined.
I can't for the life of me figure out why people would think pi is bloated.
Fullscreen mode is my only real gripe. That kind of terminal behaviour is exactly what I was trying to get away from. My work's agent (that I use Pi to replace) does this and it is annoying as all get out... but I haven't tried yours yet, so we will see. Hopefully your implementation is better!
Love pi. I tried to run some local models and pi was the only one that actually worked decently because it didn’t have a gargantuan system prompt that would take minutes to prefill on my scrawny ass laptop.
Been running it almost barebones vanilla for a couple of months. Just a bunch of basic extensions and some skills.
Now, if only they could fix the very annoying bug of the history jumping back at the beginning if I am not a the end while the model is reasoning that would great.
"Been running it almost barebones vanilla for a couple of months. Just a bunch of basic extensions and some skills."
I am also using pi exclusively after having had decent success with openhands but begrudging all of the docker infrastructure ... and all of the emojis.
My only pain point is that in my extremely common and boring workflow, which is pi inside of gnu screen inside of OSX terminal.app ... all reasoning/thinking text is blinking ... like old fashioned ANSI blink on a BBS.
I cannot figure out how to disable the blinking thought/reasoning text ...
I just fixed something very similar in my setup. Except in my case the reasoning text was shown in dark grey on a light gray background. Very ugly and hard to read.
If I remember correctly, the reasoning text was being output using the italic ANSI code, which was being formatted funny on my terminal. I fixed it by adding a font that supports italics. I recommend taking a look at the ansi codes.
I was running into similar issues where italics text was blinking. I traced it back to a bug in screen, which I patched in my own screen fork, if it’s helpful: <a href="https://github.com/Sothatsit/screen" rel="nofollow">https://github.com/Sothatsit/screen
Have you tried a different terminal app, such as Ghostty? <a href="https://ghostty.org/" rel="nofollow">https://ghostty.org/ has a Mac build, and handles italics properly. That might solve your issue without having to edit any configuration files. Plus, as a side benefit, Ghostty ignores the ANSI color codes for blinking text, so you won't ever see blinking text again.
I am wondering why people are so hyped about Ghostty? I gave it recently a try coming from kitty. And I had to configure stuff that worked out of the box with kitty, like Ctrl-Enter support and other key combos for agent harnesses. I like the development model of ghostt. And the developer really cares about creating great building blocks, e.g libghostty. But I am a bit underwhelmed.
I feel like the ghostty hype make more sense as excitement around the direction of terminal infra than a claim it is the one true terminal all others suck. Kitty's fine.
Tangentially I also kind of feel like there is some level of deification of Mitchell's products but that's a diff topic.
Apart from a different terminal app, try `/settings`, find the "TUI mode" or whatever, and set it to fullscreen. It fixed all my flickering and other issues.
Couldn't agree more. The vanilla openclaw install was this byzantine mess of MD files talking about souls and identities and such, it really put me off. Stripping back to a bare install of the underlying pi, it was delightfully minimal and easy to reason about. Excellent starting point for building an assistant agent without having to read or fight with a bunch of cruft on top.
Couple skills to integrate with an obsidian MD task tracker, small chat interface on the phone made public via tailscale, and bam, a reminder bot you can text from the grocery store.
Are you using Windows Terminal by any chance? I'm building a personal fork [0] with a patch for this exact bug (plus a few other open PRs from the upstream repo that seemed cool). Haven't tried contributing it upstream, since the patch is fully vibe-coded and I've spent almost no time trying to understand how it works, but the bug hasn't recurred since I've been using it.
You inspired me to try Pi out - so far it's worked flawlessly. Plugged it into OpenRouter and ~$.50 of Deepseek later I've installed llama.cpp and Llama 3.1. The local model doesn't work with Pi yet (and I know it will be bad and slow even if it does) but I'm curious to see what you can do on an 8GB consumer GPU these days...
> I'm curious to see what you can do on an 8GB consumer GPU these days
Running smaller 4B-7B models entirely on the GPU VRAM will get you fast inference, but you will need to scope and define the tasks well. eg, using it the model as a classifier and just feeding it from a queue.
The best performing "agent"-like model to plug into a harness that I have found so far has been Qwen3.6-35B-A3B (mixture of experts) model as I can park most of it in system RAM and CPU, while the VRAM holds the attention/shared weights.
It's definitely workable as a local AI homelab. But expect homelab levels of tuning/fiddling with it.
With the improved support for AMD GPUs I'm finally considering getting a modern 16GB card (and maybe a second one in a few years assuming prices come down)
Sure, but I'm not interested in learning about running cpp, installing CUDA, finding the right URLs for downloading llama weights. It's the best 50 cents I've spent in 20 years.
One of the dumbest sayings ever. Unless you spend all of your time doing something that makes money, the time is worth $0. You could say that you prefer to do something else during that time and would happily pay to free it up.
I thought openrouter just routes you to the same provider for the rest of the session, so that you keep hitting the same cache. Is that not the case?
Also, I’d love to use Deepseek directly (or any of the Chinese providers, at that). Seems only fair to pay the lab that built the model. Unfortunately, any requests to Chinese servers is deeply frowned upon here (Belgium, EU). For personal use: sure. As a token intelligence strategy for the company: absolutely fucking not.
I'd chime in with @rablackburn: mixture of experts is the way to go. I have a laptop with 6GB VRAM and I'm running KDE with a 4k display on the same machine, so there's only about 4 to 4.5GB actually available.
Using llama.cpp with Qwen3.6-35B-A3B or gemma4-26B-A4B gets me 200-300 tokens/s on prompt processing and 20-40 t/s output, which is good enough for me. Of course it gets slower with larger context. Interestingly gemma is faster, even though it has more active parameters.
It took a lot of parameter fiddling to get it to that speed. If you are interested I can give you some guidance on it, but I guess there are more qualified people around here.
The intelligence is good enough for simple questions and tasks (e.g. bash command howtos, asking about compiler errors, summarize something, document a code function/file, etc), but not good enough for complex things.
What quantization are you running for these? Like, you cant just run the "real" ones on your laptop right?
Wouldn't the performance of Qwen3.6-35B-A3B be drastically different if its quantized to 2b, 4b, 5b, etc? And also be effected by who did the quantization?
I am using the unsloth 4bit quants for both, with quantization aware training for gemma. I haven't tried other quants with these models. I also use a q4 quantized KV cache.
The computation is partially on the CPU (--cpu-moe) with the corresponding weights in main memory, so I could run at least gemma in 16bit precision, but I guess there's no reason to go beyond 8bit and 4 bit is deemed to be the sweet spot.
> Wouldn't the performance of Qwen3.6-35B-A3B be drastically different if its quantized to 2b, 4b, 5b, etc?
Yes. There are graphs showing the faithfulness of the logit distributions for the original and quantized versions. I think I sloth includes them in their model cards on huggingface. Usually the degradation starts small with 8b and becomes drastic for 2b. I am not sure how representative of actual quality that is though, but my guess is that it's about right, because of diminishing returns. Like, when you go from 16b to 8b you save 26GB and sacrifice (if we'll done) the least important information. But with every step you gain less and need to shave of more important things.
> And also be effected by who did the quantization?
My uninformed guess is that it makes a difference, but not as much as those who do it want you to believe.
We launched Pi support in Wasmer a few days ago and reception has been great (so you can run pi in your iPhone or browser, or embedded in Python)
We have set up this demo, if you want to try it online: <a href="https://wasmer.sh/?example=pi" rel="nofollow">https://wasmer.sh/?example=pi
(for an easter egg click on the Pi logo on the top left!)
That bug is inherent to how terminal scrollback works and can’t be fixed as long as you use it. Your only choice is that jump or stale backscroll. Or you use Pi new fullscreen mode which gives up on terminal and use alternate screens and implement own scrolling without terminal scrollback.
How do I know? I implemented my own terminal harness and faced the same issue.
I don't think it's necessarily a bug per se, but a central tradeoff in system prompt length between well-documenting the environment (harness specifics, exposed tools, tool use instructions etc) to the llm, vs the initial prompt stage ("prefill") growing so large that it results in an unpleasant lag to first response, and reduced available context, which is most noticeable with open models on resource-constrained consumer hardware.
You can use llm to optimize some of this, I condensed the tool descriptions of some larger LM Studio plugins to shrink prefill by almost 10k tokens. But there's a soft limit to this, if you don't want to under-document available tools and let the model guess (/behave unsafely).
One optimization around this is called "smart tool selection", which only sends tool descriptions when the model indicates need for a certain tool (suite), not all of them upfront.
I think you're right, but in the wrong direction. I'd imagine it's closer to a million.
- It has 3.6 million weekly NPM downloads.
- 110k GH stars.
- It's 5th (and its fork is 6th and a dependent is 8th) in monthly Openrouter tokens. Add them all together and they get close to Claude Code numbers.
There are maybe 30-60 million software developers and software developer adjacent people on this planet. Out of those probably 30% are late AI adopters, laggards, that haven't even used a terminal client and some don't even use AI.
Also a lot of people - developers included, just don't like command line tools.
Then pi is a secondary harness after Claude, Codex, OpenCode. I imagine the likelihood of pi having more than a few hundreds of thousands of users is remote. It's basically the Emacs or Vim of harnesses.
No, I definitely do not think millions of people use Emacs or Vim regularly. Vim is used more as it's available for quick config file editing on Linux.
I've been working for 20 years and I've met exactly 1 person daily driving Emacs (at least for a while), probably 10 people daily driving Vim and maybe low hundreds side arming Vim (maybe 5 for Emacs). And I've met or worked with low thousands of people at this point.
If I had to guess, probably 100 000 Vim daily drivers and maybe 20 000 Emacs daily drivers, both for extended periods of time. Dabblers probably 2-3x that at any time.
You'd see a lot more Emacs users (comparatively) in academic jobs than, let's say, web development.
As an anecdote, I worked for a network monitoring company, 90%+ of the devs were on vim. Later, I worked in a run-of-the-mill SaaS, 90%+ of the devs were on VSCode.
I'd think that (neo)vim is quite popular. Emacs, less so, that's true.
But according to the Lindy's effect, I wouldn't be surprised if VSCode disappears before Emacs and Vim.
Especially as heavy LLM users are opening their text editor less and less.
True, but I think even OpenClaw usage has falled off a cliff, plus that makes it implicit usage, most OpenClaw users probably don't care either way, it was chosen for them and they probably don't think much about it.
The thing I don't like about minimal plugin-based harnesses is that I don't always have the time to figure out which plugins and safe and sensible, and at least one of those is false more often than not when it comes to AI tools. Sorting by popular does not solve the problem.
What I did is to tell LLM to extract the functionality of the plugin I wanted into my own, simplified plugin (ditch settings I don't use, simplify dependencies).
And I ask LLMs to do so without installing naything or running any post install/clone scripts. Also ask them to scan the entire codebase of the plugin for malware or security issues.
This is how I made my own MCP plugin before pi supported it. "Clone this MCP plugin, simplify it and scan for security issues."
I’m currently building a harness for Slack to support our on-call and support channels. It’s been working great so far.
The harness is built on top of the Pi SDK. I initially used Codex, but Pi seems more hackable, and I like that it’s vendor-agnostic by default.
Running it on Kubernetes works, but dealing with the JSONL session files and making sure sessions survive pod interruptions adds some complexity. I’m using DBOS for that right now, which works well, although it still feels like overkill.
The 1.0 release came at just the right time. I’m looking forward to removing the pieces I no longer need and simplifying the architecture!
This was true maybe 8 years ago when all we had was buggy ceph drivers; but now the integration with the various cloud EBS-alikes is pretty good/seamless. VolumeSnapshots, WaitForFirstConsumer (so you're allocating in the right AZ as your STS comes up, etc etc).
It's really not all that bad anymore. I'll take going to any client and having roughly the same storage setup anyday over the hell that was the mix of enterprise sans we used to have to deal with.
Neat, but I keep having to edit the pi stub to remove the "/bin/env node" and replace that with bun instead, because, well, somehow that's still hardcoded.
I don't understand why "Cache warming for anthropic models" was not put into a standalone package, but has to be bundled with the "minimal" coding agent.
It's table stakes for using Anthropic APIs cost-consciously. They aren't building a minimal harness for nerd points; they are building it to be usable, and dogfooding it with Real Money to learn what that means realistically.
This might've made a better argument ca. 2005 wrt a 20-something Austrian's minimalist wsgi framework. Heck, I'll bet you could even find said argument somewhere in the Archive :)
That goes against the philosophy of pi. Nearly Everything is a Plugin.
Need to set the reasoning effort? Install pi-reasoning.
Need subagents? Install pi-subagents.
Need permission gating? Install one of the permission extensions (otherwise the agent can do everything).
A feature like cache warming on Anthrophic feels very strange in this environment. NOT saying that it is not useful. It just should be a plugin.
That's your philosophy of pi and it seems you are taking it from deepseek. It's stated that pi wants to keep the agent loop minimal, not the code around the harness. Also those extensions in pi can sometimes be very bad, as it depends on the maintainer. And when it comes to cache handling of the best frontier coding model, it's much better that pi itself maintains it rather than some rando online.
No I did not ask AI for this.
This is the understanding I have from working with PI for more than a year.
They also say so on their website ( <a href="https://pi.dev/" rel="nofollow">https://pi.dev/ ):
"Pi ships with powerful defaults but skips features like sub-agents and plan mode. Ask Pi to build what you want, or install a package that does it your way."
On a more serious note: pi-agent shouldn't know about such arbitrary limits imposed by a company that gets paranoid when people use thrid-party agents to consume their Claude subscriptions.
That goes against the philosophy of pi.
Nearly Everything is a Plugin.
Need to set the reasoning effort?
Install pi-reasoning.
Need subagents? Install pi-subagents.
Need permission gating? Install one of the permission extensions (otherwise the agent can do everything).
A feature like cache warming on Anthrophic feels very strange in this environment.
NOT saying that it is not useful.
It just should be a plugin.
I not saying Pi should ignore them. I am saying that for a coding agent that has been advocating leanness and minimalism and "everything is a plugin", it's outlandishly bazaar for them to include this specific functionality into the agent proper.
Yeah, it's such a subjective feature. I don't really worry about the five minute timeout, but sometimes if I'm conscious about the fact that I have an 800k token context window that I haven't interacted with for a day, I will switch to Opus for compaction and then back to Fable for interaction.
In general, though, some kind of API ping on a timeout does not support my personal workflow, which involves dozens of active or stagnant agent sessions that stay open for weeks.
If anyone's looking for something a bit more minimal, I can't recommend hax [0] enough. No MCP, agent just gets a shell tool, simple config, whole thing's in C.
I'm not sure, to be honest -- I think the main agent loop, tools, etc. are fairly standard and the main draw is fast start-up time, but it does have a very minimal default system prompt too.
That looks interesting, built it (took seconds) and it is much smaller than Pi in terms of what it needs to work (when i installed Pi in a fresh Debian container it downloaded ~500MB of stuff, which isn't exactly what i had in mind when i read it is minimalistic :-P but it is a container so i didn't care much).
I'm just running it now in its own source with Qwen 3.8 27B and llama-server and asked it to analyze the code itself. I'm mainly curious to see how it handles context compaction during tasks (what Pi does is almost seamless and AFAICT it isn't anything particularly fancy so i'd expect Hax to do something similar) and i guess asking it to analyze a whole C codebase would help trigger that with a 131,072 context. Unfortunately it seems to be missing some "context usage" indicator while it does stuff (it shows context usage in the prompt but not while working), but i guess if it does manage to analyze the C code properly, i can ask it to add that :-P and see how it fares (from my use of Pi i'm positive Qwen 3.8 27B can do all that stuff, so it'd mainly be up to the harness).
FWIW the compaction had failed again, so i used Pi with the same prompt, same model, same config to compare. The prompt was "check the current directory" followed by "analyze the code and give me a report in `CODE_REPORT.md` on how it works (also a brief report here). Make sure to update `CODE_REPORT.md` frequently (i.e. every time you analyze a file) to avoid context loss from context compaction".
Pi ended up hitting a compaction during a tool call and finished without issues, which is what i expected - in fact after giving the instruction i left to visit a relative since i expected it wouldn't need me to babysit it.
FWIW after it finished, i asked it the following:
---
Can you answer me the following questions about how Hax manages the context?
1. How does Hax handle running out of tokens? It does have some form of compaction, but if the compaction fails for some reason (e.g. the summary ends up needing more tokens) what does it do?
2. Can it handle cases where the context runs out of tokens during tool calls and if so, can it recover? How?
3. What happens with compaction if an LLM produces a few large responses or the LLM reads a few large files? Does the process ends up summarizing the entire (or all but one) conversation? Or is the entire conversation lost?
4. Are there any safeguards in place to avoid overwhelming the LLM? For example any file and tool output limits? If there is and any limits are reached, how does it handle them?
---
It went on and checked the code and, briefly the response (it was bigger but i don't want to repeat the entire thing):
1. It doesn't update the session on failure (last "good" session is kept), running out of context is treated like any other error without any automatic recovery and you're expected to fix it by hand (personally i'm not a fan of this).
2. Multiple tool calls are fine (there is a 85% threshold check to trigger compaction and a 50k tool result limit) but if a response and results jumps from below 85% to over 100% despite being under the 50k limit, it doesn't trigger any compaction and the next request is denied by the provider (i.e. llama-server). I have a feeling this is what i hit when i tried Hax with its own code.
3. There is no recovery from a user turn (prompt + response + tool result) that exceeds the window. FWIW this also seems to be the case with Pi.
4. It found a bunch of safeguards (tool output cap, caps in bytes and lines for the read tool, bash writes to a temp file and only a part of it is sent to the LLM, edit size cap, etc). AFAICT it is the same as Pi with one neat addition in that there is a default 2 minute timeout for bash calls (i've seen the LLM more than once run a command in Pi and end up stopping for 30+ minutes because the command wouldn't end).
For 3 i asked it a followup question: "About 3: AFAIK Pi (the harness you're on right now) does a "spit" summarization where the old messages are summarized up to a cutoff/split point and replaced with the summary while the newer messages after the cutoff/split point remain intact, which allow a mostly seamless transition between compactions. Does Hax do the same or something similar?"
The response was that, no, it doesn't, it summarizes the entire context. Which TBH is a bit of a dealbreaker for me since i often rely on this "seamless" continuity in my prompts and feels like the main reason why compactions feel like a non-issue with Pi.
Take the above with a grain of salt, i only checked the code for the compaction not using a split/cutoff point between older and recent messages, the rest are whatever Qwen 3.8 27B understood, but they do match my short empirical test. Also if my own understanding of the code is correct, it seems to be using the same system prompt for the summary as for regular/interactive use while AFAIK Pi uses a dedicated "you're an expert summarizer" (or something like that :-P) prompt. Not sure if it makes much or any difference, with LLMs being what they are, but TBH whatever Pi does works great IME.
On the other hand the idea of a self-contained native AI harness in C/C++ is enticing, especially one that doesn't have any network traffic outside of LLM-related stuff[0] and explicit user requests (Pi does try to autoupdate and has a separate opt-out telemetry beacon - both of which are disabled in different means, one via environment variable and another via a setting, which smells a bit like an dark pattern to me).
Anyway, this is the result of my findings about Hax. It is neat, but TBH the context handling is the main dealbreaker for me, especially since i'm often having the agent do something in the background (using a local LLM isn't exactly the speediest workflow) and do other stuff or leave the computer alone, so the last thing i want is to babysit the agent for errors. Pi's split summarization and context overflow handling seem to work much better.
For now i'll probably stick with Pi (i have autoupdates and telemetry disabled and i hope there isn't any other hidden snitch in place) and perhaps at some point i'll do the NIH thing and make yet another agent myself :-P
[0] well, it does attempt to autoconnect to a potentially running llama-server in localhost without being explicitly told to do so (Pi wants explicit configuration) but meh
I use it with a local Qwen3.8 27B on llama-server, but I don't know what it means for it exceed any window.
you can use /slots on the llama-server if you want to get more up-to-date details on session token use.
I always run models in their default context, which is 262144 for Qwen3.8 27B. I've run sessions in hax where it hit that cap multiple times and compressed the context down to 15% and continued with no problem.
> also i wonder if it works nicely if it is possible to convert Pi transcripts to Hax - i have a few "in progress" and i'd like to continue where i left from, though while both seem to use JSONL for the transcripts i'm not sure if they're compatible
You can ask the new agent to look at the previous transcript.
Or for something not quite as bare bones- batteries included and tested for token consumption- <a href="https://3code.capocasa.dev" rel="nofollow">https://3code.capocasa.dev
Nice! I've seen it around on the Nim forums. Is it terminal only or do you plan to make use of Nim's JavaScript backend at some point to make a web UI too?
I'd be very interested especially if ACP (<a href="https://agentclientprotocol.com/get-started/introduction" rel="nofollow">https://agentclientprotocol.com/get-started/introduction) was supported over stdio so when I'm not using it directly in the terminal, I could also use it in my other ACP frontends.
Pi is so good, for both running Qwen 3.8 Flash Next locally at home, and for using all the models available at my work. Shockingly useful, fast, it's TUI doesn't suck (unlike my work's own agent CLI: it's really powerful, but man that actual TUI itself is a bit rough, its too GUI-like), and extensible.
Adding MCP support is lovely, codemode sounds super interesting, and I'm super excited to take advantage of it. Now it's 1.0 I'm hoping I can convince IT to let us use it officially.
I also run Qwen3.8 Flash Next "locally at home", on a Framework Desktop, so Strix Halo and 128GB... we're not talking laptops, exactly, if that's what you wanted to know.
Still, the halogen version only occupies < 40GB RAM on my machine (which is weird... the Q4 takes over 100GB), so perhaps you could get away with a 64GB version.
A DGX Spark-like, the Asus GX10. I’m kicking myself that I didn’t buy a second one when I thought about it months ago, but Nvidia’s NVFP4 quantisation of Flash Next and offloading the ngram table to NVMe has worked well
I run Qwen3.8 Flash Next on 2x Sparks at $WORK and it has been great! It can run 16 concurrent sessions with decent speed (~30-40 t/s per session) and can hold 8 full 256k contexts in cache. It has turned out to be a great production setup for our company.
I have a half finished repo that sets it all up for production (using systemd, not hacky scripts and one-off docker commands), if someone is interested in this, tell me, and it might give me the push to actually finish up the latest threads and publish it!
Earendil, really now? Do these CEOs even like Lord Of The Rinds? Earendil sacrificed his personal future to make humanity's future better. And these guys are peddling a human replacement and sociaty disruptor (eventually) under that same name. At least Peter Thiel had the guts to pick a thematic name for his spyware, despite probably hating both Tolkien's message and humanity altogether.
How do people read these famous books and deliberately get them wrong again, and again, and again?
> despite probably hating both Tolkien's message and humanity altogether.
Everything points to Thiel not understanding a thing about Tolkien. Tolkien was an old-fashioned conservative. He was all about protecting the environment and the old way of life (both things Thiel and modern self-styled "conservatives" strive to destroy). He just does not understand the "humanity" aspect.
How do we know how different the code of pi vs opencode vs {commercial harness} is? I’m pretty happy with opencode but can’t quite understand whether I should spend the time to understand how different pi would be.
Pi is very minimal. That's the main difference between it and OpenCode. Although OpenCode has a new version called OpenCode Mini... which reminds me I told Dax I'd give it a whirl- so thanks for the reminder, stranger!
I wrote my own minimal coding harness last year because I hate software bloat, but Pi scratches that itch for me now.
Minimal alone isn’t a driving force for me. Coding intelligence and output is. I know Pete mostly codes with OC but farms hard jobs out to Codex. Teknium says he only codes in Hermes. I do iOS apps in Claude but everything else in deepseek or opus. I suspect things are about as good as they can be in terms of actual code.. across all levels.
Yeah I asked Bill Gates what he codes with in our private chat and John Carmack says he used all of them at the same time but only to check his own code while Torvalds told me he only uses it for side projects.
Out of curiosity, have you come across Axiom (<a href="https://charleswiltgen.github.io/Axiom/" rel="nofollow">https://charleswiltgen.github.io/Axiom/) in your quest for more effective AI-assisted iOS coding?
People in tech are so terrible at naming things. To clarify for anyone else, this is something to do with open software, I guess? Not the raspberry pi, and not the math concept, and not the book character and not…
I enjoyed Pi for a few weeks, but ultimately moved to other harnesses - the plugin ecosystem became a sea of slop, large vibecoded projects that don't work at all, and yet have thousands of stars. At some point I gave up.
I enjoyed Pi for a few weeks, but ultimately moved to other harnesses - the plugin ecosystem became a sea of slop, large vibecoded projects that don't work at all, and yet have thousands of stars. At some point I gave up trying.
I had the same concern last time I looked at Pi. There's no way to tell which are useful and semi-vetted and which are junk. I came to the conclusion that most people had their AI build them whatever plugin they needed, and I think this is even something they recommend.
I'd _love_ to get some feedback on how people use Pi after initial setup. I (like others) am pretty heavily "invested" in Claude Code CLI. After trying out Pi and a local model, I realized how MUCH the `claude` CLI was lifting. I'd like to strip a lot of the fluff out and build my own, but it feels like I need to see what other people are doing too.
I've recently adoped pi at work and its been a treat. I think just starting with the base agent and installing (or creating) plugins as the need arises is best. If you really want some plugins to start with pi-subagents, context-mode, and the rpiv collection are what I'd recommend.
Thanks - I think I more need to work on the prompting.. possibly. IIRC I was struggling with local operations as basic as finding files/reading files/correlating classes in the same folder.
Pi with rpiv-ask-user-question, pi-subagents (if you don't want to use tmux), pi-web-access (if you have a subscription to some search backend), plus agent-browser CLI. I don't miss anything in Claude Code.
Love it - thanks. I basically dropped into Pi, tried prompting a simple prompt (e.g. "What's the name of this project?") and realized how little it did OOTB. I know oh-my-pi exists, but I'm trying to reduce complexity for local model runs.
As someone similarly invested in Claude Code and initially reluctant to try other harnesses, I recommend the batteries-included Pi distribution oh-my-pi (omp.sh) over Pi and OpenCode. I switch between Claude Code, omp, and Codex regularly, and it feels fine.
Posted this elsewhere in this thread. I've daily driven Pi for 9+ months and I recommend pi a lot to friends. I think switching to pi from claude code is pretty daunting. The pi extension system is excellent. But which extensions should you use? And honestly a lot of the most popular extensions to me feel bloated / weird / vibe-coded.
Here's my minimal set up: <a href="https://github.com/richardgill/pi-extensions/blob/main/PI_SETUP.md" rel="nofollow">https://github.com/richardgill/pi-extensions/blob/main/PI_SE...
Congrats on the release. I'm looking forward to using Durable with some of my custom extensions and tools. The MCP specs have changed for the better, so makes sense to me with the inclusion.
A framework/harness to develop capabilities such as OpenAI dot/Grok Bot. Can handle parallel conversations/forked conversations. But it doesn’t have to be user-facing at all.
It could be used to create an agent that sits inside your infrastructure - say constantly monitoring the firewall, taking actions autonomously (within hard guardrails I hope) and leaving an audit trail.
To be clear, they say nothing about guardrails or audit trails, it’s just how I would do build something like this.
I didn't even think of that aspect of it. Just a poor little guy who sits there watching journalctl and occasionally yells when he sees something.
Awesome! Congrats on the release. As an indie developer this is big!
It addresses is a lot of pain points were built as internal tooling I maintained before this e.g. the need for a daemon for a number of good reasons e.g. executing/resuming a session from any machine, following conversations on my phone, having agents respond to comments on my CRM or asking interfacing it my homegrown PR review system. I can now have the harness run on that system and a durable pi session on a central server.
Adding MCP and code mode seems so antithetical to the minimal ethos, I almost would believe they got incentives from Jen, but I don't want to be that cynical.
I adopted Pi for both of these reasons, and the strength with which they were stated gave me the confidence to lean in.
The rationale for MCP and codemode I can swallow, Armin's writing on that makes a lot of sense, and meeting models where they are seems critical to me based on my own experience.
But for me, fullscreen mode is a _huge_ turn-off. I already have a backbuffer that I strongly prefer to use, it's called my terminal, and it's important to me. If the backbuffer-based version disappears, I'll be forced to migrate to something else (seems there are a few options here) or make my own tool, but that involves abandoning or porting my extensions, which turned out to be a huge superpower with Pi. Perhaps Pi Durable helps with that _and_ lets me keep my extensions, but I'd rather this was not necessary in the first place.
If switching to full-blown TUI has anything to do with how slow the "expand thinking" and "expand tool output" features get as the session gets longer, could that be mitigated by only expanding the _n_ most recent behind the default shortcut, and the slower "nah, I really do want you to expand them all thanks" can be a different shortcut?
If it's to add more fancy features that require fullscreen rendering and a dyed-in-the-wool terminal user like me might reasonably tolerate as a dismissable modal, make _those_ bits TUI, but keep the backbuffer in the terminal (for e.g. the session tree or the settings, those don't need to be in the terminal's scrollback).
And if it's for any other, richer interactions... can we just... not, instead, and let the terminal be the terminal rather than a single page web app?
Wish Pi (and Opencode, DeepSeek Harness, Claude, Claude Desktop, Codex Desktop) was written in a memory and performance efficient language.
I love alternatives to the big players but why is everything written in TypeScript or Python and takes up a gigabyte of ram.
I don't want to `npm install -g` something, just give me a single statically compiled binary that does the thing.
AI lowers the barrier of entry to Rust to virtually 0. As a side experiment, I have been rewriting Codex Desktop in Rust using native desktop APIs (gpui) and have made a cross platform copy that works on Windows, Linux, and MacOS. It runs at 120+fps and uses 40mb of ram. It's not that hard.
In a previous life, before the layoff times, I was working on a FaaS platform. If you need plugins, embed v8, quickjs or wasmtime/wasmer/etc.
People are acting like AI didn't eat up all the RAM on Earth. I had to sell my left kidney for the 8gb ram upgrade in my MacBook
There are Rust alternatives to pi and folks are welcome to use them.
I find Typescript more approachable in many ways like compilation speed, extensibility, disk space used by cargo, LLM knowledge, and most devs I know already have node or bun installed anyway but not cargo, including me.
The speed in which pi can modify and extend itself is part of the appeal to me.
Goose and the Pi rust rewrite are great options - but lag behind big-brand competitors in terms of token usage and generated code.
This is more about demanding more of the big software vendors than it is about making an argument for the general software developer to write programs in Rust or Go.
We are talking about trillion dollar companies with highly paid engineers and unlimited token budgets.
As someone who has been writing TypeScript since the beta and started writing Rust professionally only 5 years ago, I'm about as productive in Rust as I am in TypeScript - so if I were distributing software, I'd want to ensure the end user has the best possible experience and that's hard to achieve with the node/python ecosystem.
"Run this bash script to install my CLI tool" behind the scenes it downloads a full copy of Node.js, installs the npm dependencies, add executable scripts for the entry points, updates PATH. It takes almost a second to start up, has no threads and uses way more memory than is necessary. Extend that to Electron applications which not only bundle Chromium, but also bundle Node.js - that's two v8 engines running and a process that starts with a memory footprint of almost a gigabyte.
Compare that to just downloading a portable self-contained single executable and running it.
The end user is not installing cargo, compiling, or anything - they just run the binary.
> When was the last time you patched Pi / OpenCode / Claude dist or source code before running it?
Funny you ask. Yesterday I patched opencode to replace \ paths with / depending on some heuristics. Couldn't get a plugin to fix in all cases I needed. Solved in one minute :)
And plugins for executables just suck compared to "just create a .ts file in this directory and edit/test it in a few seconds until satisfied".
> I would need cargo to author my own Rust plugins.
Only if you wanted to write them in Rust, I guess? You could also write them in Go, TypeScript, Python, whatever.
Plugins don't need to be in the host language. It's up to the harness writer to ensure the plugin system makes sense for the patterns of plugin writers.
Then it's up to plugin writers to ensure their plugins are performant so people like using them.
> And plugins for executables suck compared to "just create a .ts file in this directory and edit/test it in a few seconds until satisfied".
Not really? Deno, Node.js are both embeddable within a native application, so plugins can be written in TypeScript without any change in expectations from the plugin dev's perspective. There's also QuickJS and LLRT which use like 1000x less resources than v8 (faster for plugins, slower for servers).
No one is asking plugin devs to change, just that the harness writers provide better platforms to build on top of
It's counterproductive to write the harness in a 2nd language if you're going to embed JS/TS runtimes. Now you need 2 toolchains since you can't just blindly generate TS code and pray it works as a plugin. Not to mention that it's much easier to reason about contracts and behavious within a single language.
You get the worst of both worlds and that's probably why the most harnesses tools don't do that.
What you're describin already exist but the target audience for such is small. I invite you to try and watch the adoption :) It's just a prompt away.
> What you're describin already exist but the target audience for such is small
I'm not sure what you're arguing for? Are you saying that you think it's acceptable that that multi-billion dollar companies with strong engineers and unlimited token budgets ship low effort products that waste the limited resources available on consumer devices?
Like, if Pi/Claude/Codex/etc used a fraction of the resources and your experience as a developer or plugin developer was unchanged - you're opposed to that?
> I invite you to try and watch the adoption :) It's just a prompt away.
I am actually writing a native harness that is a pixel perfect clone of the Codex Desktop harness haha. I expect no one to use it because adoption is not about quality, it's about marketing and that is dominated by a handful of players.
That's not going to stop me because I'm doing it for fun, but if I can do it with a handful of DeepSeek tokens and a few weekends - there's no excuse for the big players not to.
> because adoption is not about quality, it's about marketing.
Alright if you believe this then we are wasting our time arguing pros and cons of using different technologies.
I'm happy you're creating your own harness. I plan to do that too if pi gets in my way but it is so small and flexible that this has not been the case yet.
> I love alternatives to the big players but why is everything written in TypeScript or Python and takes up a gigabyte of ram.
Same reason everything's an electron app now. First mover matters to the makers and to the consumers more than performance and attention to those details.
Totally agree with this sentiment. On your plugin point, I recently did a PoC of QuickJS in wasmtime with a restrictive sandbox (10 syscalls total) for running untrusted plugin code and it was great. Took maybe 3-4 days to pull together and performed more than adequately for the kind of thing this class of software needs, with a security posture that beats pretty much anything widely deployed. When this level of engineering excellence is so cheap to achieve, we really need to bully companies that refuse to do it.
They actually mention this at the end of their post on Pi Durable[0]:
> Why TypeScript again?
Because it is the easiest way to bootstrap this. But as everybody knows by now, it's very easy to port everything to Rust or assembler. We're not ruling this out in the future, but at the moment we are focusing on TypeScript.
I wonder how Tolkien would’ve thought about the use of LotR names being used by all these AI and tech companies.. especially since they all seem to use the names of things that were corrupted by darkness.
“The Shadow that bred them can only mock, it cannot make: not real things of its own. I don't think it gave life ..., it only ruined them and twisted them.”
I wonder much the same thing, but this seems like a slightly odd place to say it since so far as I can see the only LotR name in the linked article is the company name Earendil, and AFAIK Earendil-in-Tolkien was very much not corrupted by darkness.
Well there’s <a href="https://disconnect.blog/peter-thiels-influence-over-a-network-of-lord-of-the-rings-inspired-companies/" rel="nofollow">https://disconnect.blog/peter-thiels-influence-over-a-networ... and <a href="https://www.reddit.com/r/lotr/comments/1lrc27y/how_do_tolkien_fans_feel_about_all_these_tech/" rel="nofollow">https://www.reddit.com/r/lotr/comments/1lrc27y/how_do_tolkie...
LLMs in general are a corruption in a literal moral-neutral way. You stop worrying about whether something is correct or not, or how it works and just give in to the vibes, doesn't matter what goes in the backend or in some data center or mine far away, everything reduced to producing digital nuggets.
Yes, for an encyclopedic use-case for example, asking a fact question, when compared to Google or Wikipedia, using an LLM is less deterministic and provides less auditable metadata, it's just the answer and trust me bro.
Funny that he is building a middleware layer to a biggest surveillance system in all our history, the one which will spy on everything people are typing on their digital devices forever. How nice of him :)
Though I find it funny that they put “Bearer of Light” as a description, at least on their GitHub page. AFAIK Tolkien did not used the phrase, it is maybe a bit too close to the Latin version, Lucifer. Talk about a thing corrupted by darkness.
A lot of Tolkien names come from old Germanic languages. Eärendil for example from Ēarendel, the Old English name for a figure from Norse mythology [1]
Or maybe from the 9th century poem Christ I [2], which translated to modern English starts off with the words
Hail Earendel, brightest of angels,
Sent to men over middle-earth,
And true radiance of the sun,
Fine beyond stars, you always illuminate,
From your self, every season!
IKEA catalogs using Swedish names, and Swedish being a Germanic language that stayed truer to its Germanic roots than English did, it's not that far off. In a weird way
It's so great to see now that the folks behind Pi also try to pivot away from the idea that Pi is more than a "coding" agent. Its minimalism, and tool call primitives really lends itself to be a general purpose agent for your OS that you gradually extend on demand for your specific use case.
Since January I use Pi professionally as well as personally and I can only recommend to start small and grow your harness over time. For example, for an agent in production it was so helpful for me to use Pi in interactive mode via tmux to get a feel of the agentic flow, tool calls and reasoning traces for a certain use case while only the stylized responses are rendered in Telegram via an extension to the user. As a Developer, I have full technical observability and control while providing and incrementally improving a service to a user at the same time.
Excited how Pi Durable will fit in and can support more. Congrats and thank you!
No problem, glad to ignite some spark! Just to clarify, what I mentioned is also effectively possible with other harnesses. Pi's minimalism just made it more ergonomic to focus on the right things and encouraged me to question and thus learn.
Hey thanks for posting this. I use pi professionally too. I am curious how you used agentic workflows with pi before. The simplest(since the early days) was letting it use Tmux for spawning other sessions and controlling it.
The second case, more recent, is one where I use actively now is linking pi sessions to some artifact like a code change(PR or diff) or a collection of document and then continuing the session in that context.
Especially with the extensibility of Pi, I‘m wondering whether there is a way to configure different profiles for different kinds of tasks. Such a profile would include tools, system prompt, maybe selected models and their settings.
Is there a straightforward way to do that with Pi?
Was also wondering this the other day. Every harness I’ve looked into seems to be monolithic. I would really prefer specialized profiles/configurations instead of loading up every skill and MCP server imaginable into a big stateful works-on-my-machine mess.
I just want to run `pi --profile=./gamedev.toml “build a side scroller where you’re a turtle”` and have it do the thing.
AFAIK Pi as other harnesses handles this use case via dot directories on your filesystem. So a .pi directory in your working directory Pi gets started in is the place where you would implement such a profile.
Note that there is also a global .pi in the home directory, which takes precedence over session-local .pi directories.
In the past I used this abstraction conveniently to setup different agents for different purposes. I kinda like having this abstraction on my filesystem to inspect instead of it being hidden away in a opaque harness or, even worse, the weights of the model.
Symlink the .pi directory to the profile you want, swapping changes the target of the link inste of modifying files. This is how I implement dark/light mode autoswitches on some of the cli tools I use.
I do this - one profile for work and one for personal. It’s as easy as asking Pi to build it for you. When I run Pi in specific directories it knows which profile to run, using a separate subscription and toolset.
I love Pi but I am sceptical of their claim to minimalism. New tools often make such claims as an excuse for not having a lot of features. You didn't want those features anyway! As they mature, the features and complexity creep in and before you know it, the pitch changes to more of a full stack one.
I don't mind though, because I think either way it leads to a better design under the hood when things are built to be modular.
It's not minimalistic in the way you're suggesting. Their are tons of extensions listed on pi.dev that give you all the extra features you could want. You just don't need them. The harness is very capable with just the 4 primary tools. The minimalism is a claim on the harness architecture, not the number of lines of code or the capabilities of the harness.
For the past several (months now!) I have been slowly working to open source a proxy we built for pi internally.
Its been super helpful for us, helping us centralise session logging, hook and model insights as people work on stuff. There is a bunch of other interesting things (such as runtime model evals) we now adding. If this would be of interest -- open source of course -- please drop me a note here, it will incentivise me to finally extricate it from our broader system:
I'd say it's the other way around: I like Pi because it's minimal. Not like claude code spinning up superpower:* skills, 10 background agents, etc. Also, it's a useful building block for so-called "agentic workflows" precisely because it's minimal.
The minimal setup is nice to customize per project or set of projects. Tailor made specific for the use case. Only grab extensions where necessary, I've made a few for myself and work to help me.
I did some token tests and both pi and my own 3code used 4x fewer tokens than Claude Code, while opencode used 2x fewer tokens than Claude Code. You can tell Anthropic just doesn't care about using tokens and the tradeoff is maximal performance. That's understandable, but it might not be the tradeoff you need, hence, alternative clients.
A coworker was trying to tell me that models perform better in their own agent harnesses. I use both `pi` and `omp` and I'm somewhat skeptical. I understand that the tool calls might be slightly different. But really how much impact on the model itself does the harness have?
I'm no academic, but I have read that harnesses dictate the output more than the models themselves. I'm not educated enough on the topic so I will defer to those smarter than me to chime in.
I think it's often the other way around. The differences in perceived coding productivity that many people attribute to claude vs codex is more the harness than the model it's running.
What is the harness doing that's not the model.
I've been assuming a harness is basically a set of tools and a TUI for passing text to the model and the model coming back with tool calls and user responses.
Are the tools really that complex and different between harnesses?
I have run into some models that seem to mind. Like for the life of me I couldn't get North Mini Coder to play nice on Pi, which was sad since it seemed good otherwise. It just couldn't grasp the tools.
I found this: <a href="https://arena.ai/blog/coding-agents-harness-tax" rel="nofollow">https://arena.ai/blog/coding-agents-harness-tax
Man, first MCP then this? The main reason I use Pi is because it didn't try to reinvent my terminal's buttery-smooth native scrolling -- something no terminal client can ever match.
Did you all get acquired by private equity or something? The enshittification is coming at us fast.
What does everyone do about security with this tool? Are you running it in an Nvidia sandbox (can’t recall the product name), a docker instance, or just yolo on your computer?
I'm running it a rootless podman container it set up itself while still running directly on the host. I map the .pi directory into the container so all the sessions and skills persist. Then it's just a matter of mapping the current project folder into the container.
Firecracker can be used for sandboxing. I'm not currently using the Pi + Firecracker combination but I think it's a very useful one. But the best sandbox solution probably depends on what you want to do.
Pi is great. I've been using it both personally and professionally for 10 months, give or take. I've built many personal apps that wrap the SDK — integrating it into Home Assistant and my own ChatGPT/Claude-esque web app for family and friends. Professionally, I've worked toward making it the coding interface in my company of 100+ people, with extensions that hook into our many systems, built a index of all our code and config, and built another a nice wrapper web app over the top for anyone in the company to use.
My $0.02; I use pi every day, it's always running somewhere for various kinds of tasks (no vibe coding). I run it in `sbh`, a slop cannon wrapper around `bubblewrap` that ensures that the agent only has access to things it could possibly need. The code is short and you can audit it yourself.
I run it like `sbh --net pi` or `sbh --net --docker pi` depending if I want the agent to have docker access.
I have been using OpenCode for most work related stuff now. It works well with my ChatGpt Pro subscription as well as with our locally hosted Qwen3.8.
Is it worthwhile to spend time and effort into setting up and switching to Pi? I always see people praising Pi online but I am curious to know from people who switched over from OpenCode why they did so and what I am missing.
I feel like the models work better in the more minimalist harness. It's totally anecdotal but I feel like the models get lost whenever I run them in OpenCode. Sort of like the "10x"-engineer who overengineers everything.
I' ve heard so. But I'd still consider my opinion anecdotal because I haven't done any research into the subject (or measured it myself) really. All I've done is tried both harnesses.
Pi is like archlinux of agentic harnesses; it's tinkering for the sake of tinkering. I tried it for a few weeks but didn't think it was worth the effort.
Yes, I switched from OpenCode to Pi and never looked back.
What's great with Pi is that it's very easy to extend, because it knows its own doc. So you tell it "implement a plugin that does this" and it does it directly in its own folder.
That means I have a plan mode that works exactly the way I want, I have a hook that cleans up added comments after each change, I can ask "pull this github PR and assess the comments", etc.
How does this work in practice? You type /plan and it runs something that got linked into pi, or an interpreter that can run stuff and also print back out to the terminal?
I've been avoiding investing in these kinds of tools and workflows partially because I don't understand the UX (and partially because I worry UX and tooling will change so fast that I won't get a positive ROI). Your hook sounds like a script, but your plan mode sounds like an interactive TUI, and "pull this PR and assess" sounds like a reverse proxy tool or something?
I can definitely see why the custom plan mode is useful vs just calling a script or asking the model to do something, but what's the draw to building comment cleanup and github API access into the harness vs running the comment cleanup as part of CI, or just asking the model to pull a PR and review it using gh/the web UI/the github api (with no special harness handling)? Does the model get updated with changes you make to files it already read or recently wrote?
The way I normally use coding agents is by giving them a very large task specification in a fresh session with some kind of verifiable exit criteria, and sending them off + staying out of their way. Normally I would just use other sessions or run scripts to do these things because the coding agents I've used queue any /command I give them (very frustrating when you have to wait 30+m just to check usage!) while the model is working, and in my sessions the model is working >90% of the time, so I usually have other terminal windows or applications open anyway.
1.0 releases are always more about the team saying 'we'll stop breaking things' than new features. curious if the api actually stays stable
Every few weeks Pi hits #1 here and I quietly grumble "mine does that too, but with lovely graphics.", so I'm saying it out loud: <a href="https://github.com/juggler-ai/juggler" rel="nofollow">https://github.com/juggler-ai/juggler
Like Pi, it's plugins all the way down, provider-agnostic, minimal system prompts, threaded sub-agents, code-mode, multi-client remote sessions, worktrees, a context window you can actually see and edit, etc etc
Where Pi is way ahead is the plugin ecosystem, and that takes people, which is hard to get amid the current deluge of agent action. So if there's any spare oxygen trailing off this thread, I'd love any Pi-heads who fancy a bit of GUI action to come and kick the tyres..
My personal quiet grumbling is that everyone got on the TUI bandwagon without any rational reason. I find it borderline psychotic. Or maybe humans are much more like sheep than we care to admit: we just follow the flock into the (UI) ravine. So your GUI is a nice escape.
That doesn't mean you need a TUI! Juggler runs in headless terminals and VMs - you run it as a headless server process, and it serves the exact same desktop GUI via HTTP to any number of clients
wasting_time · · focus · HN ↗
esafak · · focus · HN ↗
pizzafeelsright · · focus · HN ↗
Pi is great overall. I ended up deploying a GUI wrapper because TUI isn't as friendly to new adopters.
_pdp_ · · focus · HN ↗
<a href="https://github.com/hardbeat920/monocode" rel="nofollow">https://github.com/hardbeat920/monocode
But yes, the TUIs are supposed to be lightweight yet it is overall a horrible experience.
clickety_clack · · focus · HN ↗
Juvination · · focus · HN ↗
It kind of just gets with how you creative you want to be about it.
avazhi · · focus · HN ↗
scott01 · · focus · HN ↗
arcanemachiner · · focus · HN ↗
It's kinda a tinkerer hobby IMO. I like the freedom, but at the end of the day, it's still just a harness.
tempoponet · · focus · HN ↗
darklinear · · focus · HN ↗
lofaszvanitt · · focus · HN ↗
Winfred-zz · · focus · HN ↗
Oh My Pi comes preloaded with most stuff you need, so there's not much need to add extensions. <a href="https://github.com/can1357/oh-my-pi" rel="nofollow">https://github.com/can1357/oh-my-pi
polisaez · · focus · HN ↗
GreenWatermelon · · focus · HN ↗
For example, I started using it, wanted a plan mode, downloaded an extension for it. Wanted to be able to analyze token usage for turn in a session, I had an agent create an extension for that. Then I wanted a custom status bar, so I had an agent implement an extension for that.
jacobgold · · focus · HN ↗
I love open source. I love the terminal. I spent the last 20+ years in a terminal w/vim every single day and I'd never go back.
manav · · focus · HN ↗
phoghed · · focus · HN ↗
For research, planning, figuring out bugs, etc I usually don’t bother creating the worktree until I’ve decided on the implementation.
I’m sure there’s better workflows and software, but all I’ve got for work is gh copilot and Claude enterprise. I like copilot better than Claude for the most part.
holbrad · · focus · HN ↗
AgentMasterRace · · focus · HN ↗
phoghed · · focus · HN ↗
w-ll · · focus · HN ↗
ninininino · · focus · HN ↗
cursor.com
conductor.build
code.visualstudio.com w/ Claude Plugin or equivalent plugin
zed.dev
there are dozens tbh
techscruggs · · focus · HN ↗
AgentMasterRace · · focus · HN ↗
flaburgan · · focus · HN ↗
techscruggs · · focus · HN ↗
bibstha · · focus · HN ↗
I usually start a codex or claude session on the remote host, close my mac, even restart Orca desktop on mac, but when I start Orca, I can watch the Orca on my remote host working through.
It's similar to Claude remote session, but just easier to manage, easier to create worktree, easier to navigate, open multiple tabs etc.
sidrag22 · · focus · HN ↗
Tossed all my weekly usage for each provider at the top with their 5hour windows and such. its been great so far.
redhed · · focus · HN ↗
jacobgold · · focus · HN ↗
I usually recommend Conductor to most people. Personally, I use the one I built, but it's got a few ergonomic issues for most people which I still need to fix.
fancy_pantser · · focus · HN ↗
hakunin · · focus · HN ↗
No affiliation, just arrived at Paseo after a bunch of research.
jwpapi · · focus · HN ↗
ew-dev · · focus · HN ↗
Aperocky · · focus · HN ↗
I've eventually settled on a CLI agent multiplexer that essentially run in the background while the frontend is a GUI gateway agent to that backend system with a goal middle layer so I no longer need to interject directly into the prompts and forces the CC and Codexes to communicate to me in a structured format relevant to my purpose.
mattm · · focus · HN ↗
pkulak · · focus · HN ↗
Even if taking pride in your tools was a productivity killer (I have my doubts), maybe there's mental value to be gained.
jacobgold · · focus · HN ↗
In Oct 2026, if you're optimizing for productivity, then yes, you probably should just use both Claude and Codex and not mess around with alternatives.
If you care about other things, then have fun, no one is stopping you. Just don't pretend you're doing it because you take more "pride" or "care" in your tools. That's just silly.
jacobgold · · focus · HN ↗
If you're optimizing for productivity, then yes, you probably should just use both Claude and Codex in a GUI agent multiplexer. If you care about other things, then have fun, no one is stopping you.
trefoiled · · focus · HN ↗
personjerry · · focus · HN ↗
jLaForest · · focus · HN ↗
bayesianbot · · focus · HN ↗
mcast · · focus · HN ↗
xboxnolifes · · focus · HN ↗
arcanemachiner · · focus · HN ↗
Hell, some extensions could theoretically lower your token burn. (Like rtk, if it actually worked.)
miroljub · · focus · HN ↗
agentdev001 · · focus · HN ↗
ZeWaka · · focus · HN ↗
kelnos · · focus · HN ↗
miroljub · · focus · HN ↗
But you want to forbid those people from driving.
Do you work for Anthropic?
arcanemachiner · · focus · HN ↗
I have another one that allows you to edit the items in your Pi /tree history.
Some permission manager extensions also sit between the model and the harness, and don't actively change the tool or prompt info.
I probably have more, but you get the idea.
razster · · focus · HN ↗
I'm so use to the command keys in Pi that having to type something out in OMP slows me down. I'll stick with Pi, I've built it to my needs and having WSL finally working. I still have to run 2 CLIs, one for LLama.ccp and the other for Pi, not sure if this is normal.
rpdillon · · focus · HN ↗
omp offers some nice tools, like /shake, to manage context efficiently and offset some of that consumption.
Not sure about your point with command keys. OMP has all kinds of shortcuts and is highly configurable. It seems very unlikely that you cannot achieve what you're looking for in OMP in terms of shortcuts. Specifics would be immensely helpful here.
And yeah, you'll need to run your inference engine separately from your harness, for the same reason the web server and the web browser are different applications.
CharlesW · · focus · HN ↗
rpdillon · · focus · HN ↗
One example here is that it added MCP extensions to make the harness usable with MCP servers long before Pi figured out that that was the right move. A lot can be said about development of MCP over that timeframe, but I appreciated the bias towards adoption, since progress is driven by empirical experimentation rather than theory in this domain right now.
I've long championed assembling developer tools yourself from scratch and I've been an advocate of vanilla Emacs and customizing it yourself as an ideal developer experience (I realize this opinion is controversial). But OMP is essentially the VSCode to pi's Emacs.
I ended up choosing omp as my daily driver, mostly because I see the velocity of change in AI development being far too fast for me to make a worthwhile investment into customizing the environment myself, since that investment will have a relatively short half-life. With Linux, which I learned more than 30 years ago and still believe to be a fantastic investment, I can largely use the same knowledge I gained then to administer systems today. I fear that much investment in the specific tools that I add to my pi harness will expire before 2027. So I'm sort of drafting OMP until things settle down.
rurban · · focus · HN ↗
ZeWaka · · focus · HN ↗
amelius · · focus · HN ↗
orsorna · · focus · HN ↗
pornel · · focus · HN ↗
It automates a lot of the babysitting of agents, and lets me use a couple of smaller models with safeguards instead of burning tokens on a galaxy brain just because it listens to instructions in AGENTS.md.
alostpuppy · · focus · HN ↗
pornel · · focus · HN ↗
what · · focus · HN ↗
r14c · · focus · HN ↗
whiteblossom · · focus · HN ↗
unsnap_biceps · · focus · HN ↗
whiteblossom · · focus · HN ↗
Asooka · · focus · HN ↗
hypercube33 · · focus · HN ↗
vhantz · · focus · HN ↗
hypercube33 · · focus · HN ↗
gedy · · focus · HN ↗
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.
BeetleB · · focus · HN ↗
The only thing I've configured is the default model.
sroerick · · focus · HN ↗
ritzaco · · focus · HN ↗
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).
igorbark · · focus · HN ↗
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)_/¯
nfRfqX5n · · focus · HN ↗
sergiotapia · · focus · HN ↗
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. \
calebkaiser · · focus · HN ↗
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.
stefan_ · · focus · HN ↗
tamimio · · focus · HN ↗
razster · · focus · HN ↗
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.
andix · · focus · HN ↗
You don’t need extensions or fancy setups.
girvo · · focus · HN ↗
didibus · · focus · HN ↗
darklinear · · focus · HN ↗
culopatin · · focus · HN ↗
coopykins · · focus · HN ↗
kccqzy · · focus · HN ↗
juanre · · focus · HN ↗
lo5 · · focus · HN ↗
rurban · · focus · HN ↗
avazhi · · focus · HN ↗
Like, is this thread full of astroturfing bots? What am I reading
pavo-etc · · focus · HN ↗
stankondrat · · focus · HN ↗
Did you write your own XMPP plugin, or did you use pi-xmpp package?
<a href="https://pi.dev/packages/pi-xmpp" rel="nofollow">https://pi.dev/packages/pi-xmpp
jmcdonald-ut · · focus · HN ↗
- 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].
The light weight prompt and simple harness design are a lot of fun. I don't personally mind Claude Code, and I think it Claude Code is well designed for the problem domain, but Pi is a lot of fun to hack with.
Hope that helps!
[1]: <a href="https://mariozechner.at/posts/2025-11-30-pi-coding-agent/#toc_18" rel="nofollow">https://mariozechner.at/posts/2025-11-30-pi-coding-agent/#to...
para_parolu · · focus · HN ↗
pettijohn · · focus · HN ↗
pettijohn · · focus · HN ↗
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.
octoberfranklin · · focus · HN ↗
I have eight or nine custom extensions at varying levels of maturity, some nearing the point where sharing them becomes useful.
Because of Pi I modified my terminal (Alacritty) to support the Kitty image protocol (it already spoke sixel; Pi understandably uses the superior Kitty protocol).
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.
hermannj314 · · focus · HN ↗
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.
sagarpatil · · focus · HN ↗
ramonga · · focus · HN ↗
toadi · · focus · HN ↗
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.
mixermachine · · focus · HN ↗
ew-dev · · focus · HN ↗
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 ;-)
dozerly · · focus · HN ↗
grim_io · · focus · HN ↗
ImaCake · · focus · HN ↗
dozerly · · focus · HN ↗
igleria · · focus · HN ↗
alexfortin · · focus · HN ↗
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: <a href="https://a.l3x.in/ai" rel="nofollow">https://a.l3x.in/ai
I also maintain a couple of other Pi-related projects:
- <a href="https://awesome-pi.site/" rel="nofollow">https://awesome-pi.site/ - <a href="https://github.com/shaftoe/pi-coding-agent-action" rel="nofollow">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!
rcarmo · · focus · HN ↗
eddieroger · · focus · HN ↗
nvarsj · · focus · HN ↗
NichoPaolucci · · focus · HN ↗
Herdr is OK - but the actual interface / layout is nice. I previously would have like 6 terminals open and would lose track of which was which. I'm not super into the subagent workflows, but it's been helpful a time or two.
The only reason Herdr is just OK is because using agents to collaborate will sometimes just hijack my prompt input field. Maybe I'm using it incorrectly but I would have thought they might have a more elegant solution than that.
Computer0 · · focus · HN ↗
pizzafeelsright · · focus · HN ↗
KeplerBoy · · focus · HN ↗
hhh · · focus · HN ↗
Pi felt nice when I used it, and I do value keeping things minimal, but I just find the criteria very uneven.
rsalus · · focus · HN ↗
BeetleB · · focus · HN ↗
I don't know if you were aware, but not shipping with MCP was one of its "features":
<a href="https://mariozechner.at/posts/2025-11-02-what-if-you-dont-need-mcp/" rel="nofollow">https://mariozechner.at/posts/2025-11-02-what-if-you-dont-ne...
They let you have it via a plugin/extension.
the_mitsuhiko · · focus · HN ↗
the_mitsuhiko · · focus · HN ↗
Codex in particular is using responses lite internally and relies on codemode for parallel tool calling. So codemode was a given.
Jev on the other hand is new but it's not the first type of model we had troubles with supporting in Pi and we looked at how to make that make sense. The internal pi-ai SDK supports image generation and classifier models, but without building an extension it was never possible for you to utilize it.
So there was a while functionality of Pi that few people used, because there were no obvious ways to hook it up with the coding agent. Codemode also allows us to close that gap.
And once you have codemode, modern MCP can work quite well if the servers cooperate.
octoberfranklin · · focus · HN ↗
That is totally disappointing.
Zambyte · · focus · HN ↗
The only thing that makes Jev and the likes particularly interesting is that it is a general purpose classifier. In the past, classification tasks meant training a new model to solve your problem. Now you can just use an off the shelf general purpose model and hit the ground running.
charcircuit · · focus · HN ↗
the_mitsuhiko · · focus · HN ↗
Codemode as a mechanism can expose non LLM functionality to the coding agent. In that sense, Pi does not have a tool for Jev or other classifiers. It just now makes it easier for the agent to utilize it in the same way as it's otherwise quite creative in using bash.
charcircuit · · focus · HN ↗
The point of Pi is that the user can tell the agent to improve itself and give it the tools it does need. The minimalism comes from the user creating what they need instead of the maintainers trying to support everything for the users.
pkulak · · focus · HN ↗
charcircuit · · focus · HN ↗
the_mitsuhiko · · focus · HN ↗
The point of Pi is to be minimal but also follow what the models need. We were pretty outspoken that models need code execution, and that's why Pi to this day has a very small set of tools available. However as more and more training with these models abstracts even over toolcalls themselves with code mode and similar things, it requires changes to Pi.
Mario and I talked about this last week if you want to know our thinking: <a href="https://x.com/pidotdev/status/2104510506627121451" rel="nofollow">https://x.com/pidotdev/status/2104510506627121451
And yes, that's why there is no Jev tool in Pi either.
coldtea · · focus · HN ↗
alex7o · · focus · HN ↗
Foobar8568 · · focus · HN ↗
alex7o · · focus · HN ↗
luipugs · · focus · HN ↗
mrkn1 · · focus · HN ↗
prometheus1992 · · focus · HN ↗
General purpose classifiers have existed and proven useful for quite a while now. We used these last year. for vision and text both.
bathtub365 · · focus · HN ↗
doormatt · · focus · HN ↗
strangecasts · · focus · HN ↗
[dead]
tel · · focus · HN ↗
peab · · focus · HN ↗
vinhnx · · focus · HN ↗
<a href="https://github.com/vinhnx/vtcode" rel="nofollow">https://github.com/vinhnx/vtcode
extr · · focus · HN ↗
Aperocky · · focus · HN ↗
If there's anything that I can conclude about Anthropics idea of how a LLM should speak. Vibes would have been an euphemism
alexhans · · focus · HN ↗
Some tools used to be 0.x for ages and, in this case, the 1.0 signals they're happy enough and allows them to promote things in a better way.
This is I guess the natural evolution of playing around building temporal like things for a need that many have.
ryanisnan · · focus · HN ↗
andix · · focus · HN ↗
bel8 · · focus · HN ↗
I used MCP extension but recently it added builtin support for MCP so my stack is simpler nopw.
Thank you for keeping things simple! Simple is beautiful.
vblanco · · focus · HN ↗
smokel · · focus · HN ↗
Somehow, I find that number hard to believe. The project has a lot of GitHub stars and lot of npm downloads, but my dog isn't using it yet.
rickreynoldssf · · focus · HN ↗
sgustard · · focus · HN ↗
the_mitsuhiko · · focus · HN ↗
micromacrofoot · · focus · HN ↗
bigmadshoe · · focus · HN ↗
jszymborski · · focus · HN ↗
sroerick · · focus · HN ↗
I also like Autolith. The freedom of having a lisp machine is, to me, much more enjoyable than trying to maintain Typescript. But I'm not a typescript guy.
I do largely stick with Pi because it's very bulletproofed
rcarmo · · focus · HN ↗
sroerick · · focus · HN ↗
dugidugout · · focus · HN ↗
Zambyte · · focus · HN ↗
sroerick · · focus · HN ↗
0gs · · focus · HN ↗
aliasxneo · · focus · HN ↗
jszymborski · · focus · HN ↗
dolebirchwood · · focus · HN ↗
jszymborski · · focus · HN ↗
Now I just write a prompt and OMP just hammers away at it. There might very well be some OpenCode plugin for this but it just works out of the box with OMP.
pmoriarty · · focus · HN ↗
omp is feature rich, and it's very actively developed. I don't have the time or interest to pick and choose among the thousands of pi extensions, so the fact that omp already has a lot of useful things built it is a good match for me.
pornel · · focus · HN ↗
OMP spawns agents asynchronously, letting the main agent check on them periodically and even chat back and forth with the subagents to coordinate dynamically instead of losing control after initial prompt (it's also very amusing, like watching Sims play office).
OMP also has /tan tangential prompt which spawns subagents that reuse entire conversation prefix (cached), so you don't waste tokens on sending them a recap of the situation and them re-discovering the codebase themselves. OpenCode kinda does it with fork + switch of sessions, but a command inside one session is quicker.
Footprint0521 · · focus · HN ↗
roger_ · · focus · HN ↗
aliasxneo · · focus · HN ↗
Haven't used omp web yet.
stavros · · focus · HN ↗
asar · · focus · HN ↗
lionkor · · focus · HN ↗
semiquaver · · focus · HN ↗
pezgordo · · focus · HN ↗
Languages with less opensource footprint or too verbose are at the losing side in a llm-driven world.
nicce · · focus · HN ↗
semiquaver · · focus · HN ↗
> most of their time waiting for the models response and tool calling rather than running their code.
You’d think that! Yet claude-code spends a very surprising amount of CPU just doing text layout work and other mysterious things, likely due to their decision to use React to build a TUI for some reason.
Zambyte · · focus · HN ↗
semiquaver · · focus · HN ↗
Zambyte · · focus · HN ↗
nicce · · focus · HN ↗
And yes, API must be maintained for compatibility, but that is needed anyway.
ricardobeat · · focus · HN ↗
arecsu · · focus · HN ↗
droidjj · · focus · HN ↗
On the other hand, I don't think there's anything Pi does that another language would do noticeably better from a user's perspective. Any performance complaints I have using Pi come from twiddling my thumbs waiting for Sam Altman's servers to bestow tokens upon me.
At any rate, they'll probably have Opus 6.5 and GPT-7 Galactica rewrite it in rust in a couple months...
crooked-v · · focus · HN ↗
razster · · focus · HN ↗
sieve · · focus · HN ↗
TS probably has the most expressive type system of any language that I have used, and you can develop at lightning speed without fighting the borrow checker or anything else. The ability to share the exact same code across the front and back end, and encode API contracts in the type system, is a superpower for webapps built with node.
Whether an LLM writes the code or not is besides the point. What matters is that the code should be testable, and understandable. TS wins on both counts, like most sane alternatives.
I personally do not program using any language that does not have the ability to specify types.
Maxforever · · focus · HN ↗
jazzypants · · focus · HN ↗
semiquaver · · focus · HN ↗
jazzypants · · focus · HN ↗
imnotr0b0t · · focus · HN ↗
MisterBiggs · · focus · HN ↗
ad_fontes · · focus · HN ↗
I actually built my own tool that maintains a work graph (DAG-like) with task leases. It allows me to copy and paste pre-written prompts into Claude Code, Codex, or OpenCode and all the agents self-coordinate through MCP calls.
I built this after trying hermes and Openclaw but not liking the lack of human-in-the-loop judgement. So I'm wondering if I should keep refining my tool, or evaluate something like pi?
popalchemist · · focus · HN ↗
svintus · · focus · HN ↗
smokel · · focus · HN ↗
Minimalism is a difficult subject. In art, minimalists tried to strive for something that is universally minimal. But if you look in nature for straight lines or perfect circles, you end up disappointed. Turns out minimalism found things that were minimal with respect to humans.
slickytail · · focus · HN ↗
athrowaway3z · · focus · HN ↗
saagarjha · · focus · HN ↗
bibstha · · focus · HN ↗
bakies · · focus · HN ↗
fancy_pantser · · focus · HN ↗
k4rnaj1k · · focus · HN ↗
[dead]
wgd · · focus · HN ↗
badlogic · · focus · HN ↗
I did not read this when I added support for AGENTS.md, skills, llama.cpp, extensions, alt TUI mode, mid-convo system messages and tool set changes to preserve KV cache, image model support, and everything else I added since November last year.
Codemode and MCP support are the latest additions. We follow what the models are trained on. E.g. the GPT family of models is actually trained on codemode for parallel tool calls now. The MCP spec has gotten a major update recently that makes it much less bad than it used to be in the past 24 months. Combined with codemode, it is now passable, so it got added to pi.
All of these features are still entirely optional and the only thing I could think of that could be considered "bloat" is the additional few megabytes for the QuickJS WASM blob.
So, I mean this in earenst and absolutely not combative: could you explain what exactly flips the switch between "pi is minimal" and "pi is not minimal"?
wgd · · focus · HN ↗
That said I also dislike many of those other changes and would prefer a hypothetical version of Pi which didn't have them, so this is in some sense just me looking up at the sound of a v1.0 release and realizing "oh hey, I don't really like the direction this has been trending for a while"
badlogic · · focus · HN ↗
mijoharas · · focus · HN ↗
The codemode stuff/mcp has been explained to death at this point but I haven't seen anything around fullscreen.
(I don't have strong feelings either way, just curious)
badlogic · · focus · HN ↗
I wanted the out of the box experience to be smoother for more people, so made it the default. Scrollback mode will stay though for users who prefer it.
steezeburger · · focus · HN ↗
If only there was some way to... ah no time to be snarky. It's open source and MIT licensed and you're in a thread discussing AI coding agents.
realty_geek · · focus · HN ↗
Sounds to me like things people say just to have something to say. True, it is good to listen to feedback but feedback without evidence is only going to waste your time.
Thanks for all your hard work and keep going in the direction that makes sense to you!
rcarmo · · focus · HN ↗
I can't for the life of me figure out why people would think pi is bloated.
girvo · · focus · HN ↗
badlogic · · focus · HN ↗
it's still there and won't get removed.
girvo · · focus · HN ↗
capocasa · · focus · HN ↗
<a href="https://3code.capocasa.dev" rel="nofollow">https://3code.capocasa.dev
I believe software can be done- with incremental improvement and keeping the foundation, like vim. That's the 3code trajectory.
New fun ideas go into seperate tools, possibly ones 3code (or other minimal agents) can call, but the core stays lean.
FacelessJim · · focus · HN ↗
Been running it almost barebones vanilla for a couple of months. Just a bunch of basic extensions and some skills.
Now, if only they could fix the very annoying bug of the history jumping back at the beginning if I am not a the end while the model is reasoning that would great.
rsync · · focus · HN ↗
I am also using pi exclusively after having had decent success with openhands but begrudging all of the docker infrastructure ... and all of the emojis.
My only pain point is that in my extremely common and boring workflow, which is pi inside of gnu screen inside of OSX terminal.app ... all reasoning/thinking text is blinking ... like old fashioned ANSI blink on a BBS.
I cannot figure out how to disable the blinking thought/reasoning text ...
cbsks · · focus · HN ↗
If I remember correctly, the reasoning text was being output using the italic ANSI code, which was being formatted funny on my terminal. I fixed it by adding a font that supports italics. I recommend taking a look at the ansi codes.
rsync · · focus · HN ↗
This seems like an obvious configuration option - I can imagine someone disliking the italics as well…
nine_k · · focus · HN ↗
stpedgwdgfhgdd · · focus · HN ↗
Perhaps Pi should ask after x days of installation; is there anything I can do to make the interaction better?
lionkor · · focus · HN ↗
jasonjayr · · focus · HN ↗
That line is in the startup message everytime...
throwawayblahbl · · focus · HN ↗
[dead]
sothatsit · · focus · HN ↗
rpdillon · · focus · HN ↗
rmunn · · focus · HN ↗
funcDropShadow · · focus · HN ↗
alxhslm · · focus · HN ↗
Came from iTerm2, and Ghostty is much faster and minimal.
computershit · · focus · HN ↗
Tangentially I also kind of feel like there is some level of deification of Mitchell's products but that's a diff topic.
nine_k · · focus · HN ↗
huijzer · · focus · HN ↗
dvergeylen · · focus · HN ↗
kalleboo · · focus · HN ↗
jonwinstanley · · focus · HN ↗
Geezus_42 · · focus · HN ↗
lionkor · · focus · HN ↗
RickS · · focus · HN ↗
Couple skills to integrate with an obsidian MD task tracker, small chat interface on the phone made public via tailscale, and bam, a reminder bot you can text from the grocery store.
AgentMasterRace · · focus · HN ↗
vergessenmir · · focus · HN ↗
davedx · · focus · HN ↗
vorticalbox · · focus · HN ↗
This is what I did and then just wrote small skills so now pi can read and send messages for me.
Medea · · focus · HN ↗
berofeev · · focus · HN ↗
wilt_ · · focus · HN ↗
[0] <a href="https://github.com/wilt00/windows-terminal/releases" rel="nofollow">https://github.com/wilt00/windows-terminal/releases
simpaticoder · · focus · HN ↗
sejje · · focus · HN ↗
Nothing, really. Might be coming soon, but no.
You probably want to try bonsai, I guess, but don't expect good results.
aktenlage · · focus · HN ↗
rablackburn · · focus · HN ↗
Running smaller 4B-7B models entirely on the GPU VRAM will get you fast inference, but you will need to scope and define the tasks well. eg, using it the model as a classifier and just feeding it from a queue.
The best performing "agent"-like model to plug into a harness that I have found so far has been Qwen3.6-35B-A3B (mixture of experts) model as I can park most of it in system RAM and CPU, while the VRAM holds the attention/shared weights.
It's definitely workable as a local AI homelab. But expect homelab levels of tuning/fiddling with it.
With the improved support for AMD GPUs I'm finally considering getting a modern 16GB card (and maybe a second one in a few years assuming prices come down)
what · · focus · HN ↗
You could install this yourself for free? I get $0.50 isn’t all that much, but still?
simpaticoder · · focus · HN ↗
8n4vidtmkvmk · · focus · HN ↗
But AI for installing tricky opensource software is indeed a good use case. I do that too.
AgentMasterRace · · focus · HN ↗
Kurtz79 · · focus · HN ↗
Even if you spend just 10 minutes of it, I would argue $0.50 it's not a bad deal.
what · · focus · HN ↗
One of the dumbest sayings ever. Unless you spend all of your time doing something that makes money, the time is worth $0. You could say that you prefer to do something else during that time and would happily pay to free it up.
whatshisface · · focus · HN ↗
simpaticoder · · focus · HN ↗
lemontheme · · focus · HN ↗
Also, I’d love to use Deepseek directly (or any of the Chinese providers, at that). Seems only fair to pay the lab that built the model. Unfortunately, any requests to Chinese servers is deeply frowned upon here (Belgium, EU). For personal use: sure. As a token intelligence strategy for the company: absolutely fucking not.
miek · · focus · HN ↗
[dead]
gigatexal · · focus · HN ↗
RussianCow · · focus · HN ↗
cellularmitosis · · focus · HN ↗
aktenlage · · focus · HN ↗
Using llama.cpp with Qwen3.6-35B-A3B or gemma4-26B-A4B gets me 200-300 tokens/s on prompt processing and 20-40 t/s output, which is good enough for me. Of course it gets slower with larger context. Interestingly gemma is faster, even though it has more active parameters.
It took a lot of parameter fiddling to get it to that speed. If you are interested I can give you some guidance on it, but I guess there are more qualified people around here.
The intelligence is good enough for simple questions and tasks (e.g. bash command howtos, asking about compiler errors, summarize something, document a code function/file, etc), but not good enough for complex things.
GCUMstlyHarmls · · focus · HN ↗
What quantization are you running for these? Like, you cant just run the "real" ones on your laptop right?
Wouldn't the performance of Qwen3.6-35B-A3B be drastically different if its quantized to 2b, 4b, 5b, etc? And also be effected by who did the quantization?
aktenlage · · focus · HN ↗
The computation is partially on the CPU (--cpu-moe) with the corresponding weights in main memory, so I could run at least gemma in 16bit precision, but I guess there's no reason to go beyond 8bit and 4 bit is deemed to be the sweet spot.
GCUMstlyHarmls · · focus · HN ↗
aktenlage · · focus · HN ↗
Yes. There are graphs showing the faithfulness of the logit distributions for the original and quantized versions. I think I sloth includes them in their model cards on huggingface. Usually the degradation starts small with 8b and becomes drastic for 2b. I am not sure how representative of actual quality that is though, but my guess is that it's about right, because of diminishing returns. Like, when you go from 16b to 8b you save 26GB and sacrifice (if we'll done) the least important information. But with every step you gain less and need to shave of more important things.
> And also be effected by who did the quantization?
My uninformed guess is that it makes a difference, but not as much as those who do it want you to believe.
Otterly99 · · focus · HN ↗
- <a href="https://huggingface.co/unsloth/Qwen3.5-9B-GGUF" rel="nofollow">https://huggingface.co/unsloth/Qwen3.5-9B-GGUF - <a href="https://huggingface.co/empero-ai/Qwen3.8-9B-Distill-GGUF" rel="nofollow">https://huggingface.co/empero-ai/Qwen3.8-9B-Distill-GGUF (unofficial Qwen 3.8-9B) - <a href="https://huggingface.co/ornith-ai/Ornith-1.5-9B-GGUF" rel="nofollow">https://huggingface.co/ornith-ai/Ornith-1.5-9B-GGUF (my personnal favorite)
Godsend69 · · focus · HN ↗
[dead]
crossroadsguy · · focus · HN ↗
gchamonlive · · focus · HN ↗
gigatexal · · focus · HN ↗
andriy_koval · · focus · HN ↗
I use agy and codex, and don't see strong difference in ui quality.
gchamonlive · · focus · HN ↗
ziphyrien · · focus · HN ↗
However, they have now set full-screen mode as the default.
syrusakbary · · focus · HN ↗
We launched Pi support in Wasmer a few days ago and reception has been great (so you can run pi in your iPhone or browser, or embedded in Python)
We have set up this demo, if you want to try it online: <a href="https://wasmer.sh/?example=pi" rel="nofollow">https://wasmer.sh/?example=pi
(for an easter egg click on the Pi logo on the top left!)
dmarchand90 · · focus · HN ↗
miroljub · · focus · HN ↗
How do I know? I implemented my own terminal harness and faced the same issue.
kelnos · · focus · HN ↗
smokel · · focus · HN ↗
Or is it a non-trivial bug that requires a lot of refactoring, and could introduce a lot of new bugs? That would require careful review from a human.
The latter may well be a reason why I don't see extreme productivity gains in larger brown-field projects.
(Disclaimer: I see enormous benefits in one-off greenfield projects.)
kekebo · · focus · HN ↗
You can use llm to optimize some of this, I condensed the tool descriptions of some larger LM Studio plugins to shrink prefill by almost 10k tokens. But there's a soft limit to this, if you don't want to under-document available tools and let the model guess (/behave unsafely).
One optimization around this is called "smart tool selection", which only sends tool descriptions when the model indicates need for a certain tool (suite), not all of them upfront.
WA · · focus · HN ↗
pkulak · · focus · HN ↗
distantsounds · · focus · HN ↗
randomperson321 · · focus · HN ↗
concrete_head · · focus · HN ↗
Wheen · · focus · HN ↗
- It has 3.6 million weekly NPM downloads.
- 110k GH stars.
- It's 5th (and its fork is 6th and a dependent is 8th) in monthly Openrouter tokens. Add them all together and they get close to Claude Code numbers.
oblio · · focus · HN ↗
There are maybe 30-60 million software developers and software developer adjacent people on this planet. Out of those probably 30% are late AI adopters, laggards, that haven't even used a terminal client and some don't even use AI.
Also a lot of people - developers included, just don't like command line tools.
Then pi is a secondary harness after Claude, Codex, OpenCode. I imagine the likelihood of pi having more than a few hundreds of thousands of users is remote. It's basically the Emacs or Vim of harnesses.
razster · · focus · HN ↗
oblio · · focus · HN ↗
aitchnyu · · focus · HN ↗
pessimizer · · focus · HN ↗
oblio · · focus · HN ↗
I've been working for 20 years and I've met exactly 1 person daily driving Emacs (at least for a while), probably 10 people daily driving Vim and maybe low hundreds side arming Vim (maybe 5 for Emacs). And I've met or worked with low thousands of people at this point.
If I had to guess, probably 100 000 Vim daily drivers and maybe 20 000 Emacs daily drivers, both for extended periods of time. Dabblers probably 2-3x that at any time.
AloysB · · focus · HN ↗
You'd see a lot more Emacs users (comparatively) in academic jobs than, let's say, web development.
As an anecdote, I worked for a network monitoring company, 90%+ of the devs were on vim. Later, I worked in a run-of-the-mill SaaS, 90%+ of the devs were on VSCode.
I'd think that (neo)vim is quite popular. Emacs, less so, that's true.
But according to the Lindy's effect, I wouldn't be surprised if VSCode disappears before Emacs and Vim. Especially as heavy LLM users are opening their text editor less and less.
Wheen · · focus · HN ↗
Though, I realize now the "hundreds of thousands" claim I was responding to is per week, while my guess is all time.
oblio · · focus · HN ↗
True, but I think even OpenClaw usage has falled off a cliff, plus that makes it implicit usage, most OpenClaw users probably don't care either way, it was chosen for them and they probably don't think much about it.
verdverm · · focus · HN ↗
Mashimo · · focus · HN ↗
Not a proof, but that makes it sound more plausible, no?
platinumrad · · focus · HN ↗
bel8 · · focus · HN ↗
And I ask LLMs to do so without installing naything or running any post install/clone scripts. Also ask them to scan the entire codebase of the plugin for malware or security issues.
This is how I made my own MCP plugin before pi supported it. "Clone this MCP plugin, simplify it and scan for security issues."
trvz · · focus · HN ↗
the_mitsuhiko · · focus · HN ↗
amelius · · focus · HN ↗
abirch · · focus · HN ↗
I'm getting ~/.bun/install/global:bun update @earendil-works/pi-coding-agent@latest bun update v1.4.2 (744846f84) error: refusing to install dependency get-ripgrep with unsafe folder path "../../third_party/get-ripgrep"
azuanrb · · focus · HN ↗
The harness is built on top of the Pi SDK. I initially used Codex, but Pi seems more hackable, and I like that it’s vendor-agnostic by default.
Running it on Kubernetes works, but dealing with the JSONL session files and making sure sessions survive pod interruptions adds some complexity. I’m using DBOS for that right now, which works well, although it still feels like overkill.
The 1.0 release came at just the right time. I’m looking forward to removing the pieces I no longer need and simplifying the architecture!
lukebuehler · · focus · HN ↗
cannonpalms · · focus · HN ↗
cyberpunk · · focus · HN ↗
It's really not all that bad anymore. I'll take going to any client and having roughly the same storage setup anyday over the hell that was the mix of enterprise sans we used to have to deal with.
1ahf-qzwt · · focus · HN ↗
Maybe spend $100,000 in tokens to fix that.
micromacrofoot · · focus · HN ↗
rcarmo · · focus · HN ↗
utilize1808 · · focus · HN ↗
threecheese · · focus · HN ↗
This might've made a better argument ca. 2005 wrt a 20-something Austrian's minimalist wsgi framework. Heck, I'll bet you could even find said argument somewhere in the Archive :)
mixermachine · · focus · HN ↗
That goes against the philosophy of pi. Nearly Everything is a Plugin. Need to set the reasoning effort? Install pi-reasoning. Need subagents? Install pi-subagents. Need permission gating? Install one of the permission extensions (otherwise the agent can do everything).
A feature like cache warming on Anthrophic feels very strange in this environment. NOT saying that it is not useful. It just should be a plugin.
kelnos · · focus · HN ↗
mixermachine · · focus · HN ↗
Good thing I can remove another package.
endinator · · focus · HN ↗
mixermachine · · focus · HN ↗
They also say so on their website ( <a href="https://pi.dev/" rel="nofollow">https://pi.dev/ ): "Pi ships with powerful defaults but skips features like sub-agents and plan mode. Ask Pi to build what you want, or install a package that does it your way."
ruined · · focus · HN ↗
i guess you could blame the api, if you wanted.
utilize1808 · · focus · HN ↗
On a more serious note: pi-agent shouldn't know about such arbitrary limits imposed by a company that gets paranoid when people use thrid-party agents to consume their Claude subscriptions.
shepherdjerred · · focus · HN ↗
what · · focus · HN ↗
mixermachine · · focus · HN ↗
A feature like cache warming on Anthrophic feels very strange in this environment. NOT saying that it is not useful. It just should be a plugin.
utilize1808 · · focus · HN ↗
jonwinstanley · · focus · HN ↗
Hamuko · · focus · HN ↗
tcdent · · focus · HN ↗
In general, though, some kind of API ping on a timeout does not support my personal workflow, which involves dozens of active or stagnant agent sessions that stay open for weeks.
ltrg · · focus · HN ↗
[0] <a href="https://usehax.dev/" rel="nofollow">https://usehax.dev/
exe34 · · focus · HN ↗
ltrg · · focus · HN ↗
badsectoracula · · focus · HN ↗
I'm just running it now in its own source with Qwen 3.8 27B and llama-server and asked it to analyze the code itself. I'm mainly curious to see how it handles context compaction during tasks (what Pi does is almost seamless and AFAICT it isn't anything particularly fancy so i'd expect Hax to do something similar) and i guess asking it to analyze a whole C codebase would help trigger that with a 131,072 context. Unfortunately it seems to be missing some "context usage" indicator while it does stuff (it shows context usage in the prompt but not while working), but i guess if it does manage to analyze the C code properly, i can ask it to add that :-P and see how it fares (from my use of Pi i'm positive Qwen 3.8 27B can do all that stuff, so it'd mainly be up to the harness).
badsectoracula · · focus · HN ↗
Pi ended up hitting a compaction during a tool call and finished without issues, which is what i expected - in fact after giving the instruction i left to visit a relative since i expected it wouldn't need me to babysit it.
FWIW after it finished, i asked it the following:
---
Can you answer me the following questions about how Hax manages the context?
1. How does Hax handle running out of tokens? It does have some form of compaction, but if the compaction fails for some reason (e.g. the summary ends up needing more tokens) what does it do?
2. Can it handle cases where the context runs out of tokens during tool calls and if so, can it recover? How?
3. What happens with compaction if an LLM produces a few large responses or the LLM reads a few large files? Does the process ends up summarizing the entire (or all but one) conversation? Or is the entire conversation lost?
4. Are there any safeguards in place to avoid overwhelming the LLM? For example any file and tool output limits? If there is and any limits are reached, how does it handle them?
---
It went on and checked the code and, briefly the response (it was bigger but i don't want to repeat the entire thing):
1. It doesn't update the session on failure (last "good" session is kept), running out of context is treated like any other error without any automatic recovery and you're expected to fix it by hand (personally i'm not a fan of this).
2. Multiple tool calls are fine (there is a 85% threshold check to trigger compaction and a 50k tool result limit) but if a response and results jumps from below 85% to over 100% despite being under the 50k limit, it doesn't trigger any compaction and the next request is denied by the provider (i.e. llama-server). I have a feeling this is what i hit when i tried Hax with its own code.
3. There is no recovery from a user turn (prompt + response + tool result) that exceeds the window. FWIW this also seems to be the case with Pi.
4. It found a bunch of safeguards (tool output cap, caps in bytes and lines for the read tool, bash writes to a temp file and only a part of it is sent to the LLM, edit size cap, etc). AFAICT it is the same as Pi with one neat addition in that there is a default 2 minute timeout for bash calls (i've seen the LLM more than once run a command in Pi and end up stopping for 30+ minutes because the command wouldn't end).
For 3 i asked it a followup question: "About 3: AFAIK Pi (the harness you're on right now) does a "spit" summarization where the old messages are summarized up to a cutoff/split point and replaced with the summary while the newer messages after the cutoff/split point remain intact, which allow a mostly seamless transition between compactions. Does Hax do the same or something similar?"
The response was that, no, it doesn't, it summarizes the entire context. Which TBH is a bit of a dealbreaker for me since i often rely on this "seamless" continuity in my prompts and feels like the main reason why compactions feel like a non-issue with Pi.
Take the above with a grain of salt, i only checked the code for the compaction not using a split/cutoff point between older and recent messages, the rest are whatever Qwen 3.8 27B understood, but they do match my short empirical test. Also if my own understanding of the code is correct, it seems to be using the same system prompt for the summary as for regular/interactive use while AFAIK Pi uses a dedicated "you're an expert summarizer" (or something like that :-P) prompt. Not sure if it makes much or any difference, with LLMs being what they are, but TBH whatever Pi does works great IME.
On the other hand the idea of a self-contained native AI harness in C/C++ is enticing, especially one that doesn't have any network traffic outside of LLM-related stuff[0] and explicit user requests (Pi does try to autoupdate and has a separate opt-out telemetry beacon - both of which are disabled in different means, one via environment variable and another via a setting, which smells a bit like an dark pattern to me).
Anyway, this is the result of my findings about Hax. It is neat, but TBH the context handling is the main dealbreaker for me, especially since i'm often having the agent do something in the background (using a local LLM isn't exactly the speediest workflow) and do other stuff or leave the computer alone, so the last thing i want is to babysit the agent for errors. Pi's split summarization and context overflow handling seem to work much better.
For now i'll probably stick with Pi (i have autoupdates and telemetry disabled and i hope there isn't any other hidden snitch in place) and perhaps at some point i'll do the NIH thing and make yet another agent myself :-P
[0] well, it does attempt to autoconnect to a potentially running llama-server in localhost without being explicitly told to do so (Pi wants explicit configuration) but meh
tingletech · · focus · HN ↗
you can use /slots on the llama-server if you want to get more up-to-date details on session token use.
I always run models in their default context, which is 262144 for Qwen3.8 27B. I've run sessions in hax where it hit that cap multiple times and compressed the context down to 15% and continued with no problem.
collinmanderson · · focus · HN ↗
You can ask the new agent to look at the previous transcript.
octoberfranklin · · focus · HN ↗
Pi's selling point used to be: no MCP, native scrollback.
Now Pi is a fullscreen TUI with built-in MCP.
capocasa · · focus · HN ↗
aquariusDue · · focus · HN ↗
capocasa · · focus · HN ↗
Yes- I plan to make a a full web app, as well as a web-and-terminal orchestrator app. Still planning the details.
VGHN7XDuOXPAzol · · focus · HN ↗
k__ · · focus · HN ↗
Can you elaborate?
What are the decisions that lead to this difference and what are their pros and cons?
I noticed Pi being chatty, but I assumes this was a model issue (DS4.1F).
andix · · focus · HN ↗
girvo · · focus · HN ↗
Adding MCP support is lovely, codemode sounds super interesting, and I'm super excited to take advantage of it. Now it's 1.0 I'm hoping I can convince IT to let us use it officially.
Zambyte · · focus · HN ↗
solaire_oa · · focus · HN ↗
Still, the halogen version only occupies < 40GB RAM on my machine (which is weird... the Q4 takes over 100GB), so perhaps you could get away with a 64GB version.
girvo · · focus · HN ↗
rsolva · · focus · HN ↗
I have a half finished repo that sets it all up for production (using systemd, not hacky scripts and one-off docker commands), if someone is interested in this, tell me, and it might give me the push to actually finish up the latest threads and publish it!
2001zhaozhao · · focus · HN ↗
Yizahi · · focus · HN ↗
How do people read these famous books and deliberately get them wrong again, and again, and again?
<a href="https://www.youtube.com/watch?v=pBbDxDOV6J4" rel="nofollow">https://www.youtube.com/watch?v=pBbDxDOV6J4 (relevant comedy skit)
kergonath · · focus · HN ↗
Everything points to Thiel not understanding a thing about Tolkien. Tolkien was an old-fashioned conservative. He was all about protecting the environment and the old way of life (both things Thiel and modern self-styled "conservatives" strive to destroy). He just does not understand the "humanity" aspect.
toephu2 · · focus · HN ↗
CharlesW · · focus · HN ↗
Adding insult to injury, Pi apparently considers low Tolkien usage to be beneficial.
fhn · · focus · HN ↗
browningstreet · · focus · HN ↗
floydnoel · · focus · HN ↗
I wrote my own minimal coding harness last year because I hate software bloat, but Pi scratches that itch for me now.
browningstreet · · focus · HN ↗
Is that part of opencode v2?
Minimal alone isn’t a driving force for me. Coding intelligence and output is. I know Pete mostly codes with OC but farms hard jobs out to Codex. Teknium says he only codes in Hermes. I do iOS apps in Claude but everything else in deepseek or opus. I suspect things are about as good as they can be in terms of actual code.. across all levels.
rolymath · · focus · HN ↗
browningstreet · · focus · HN ↗
CharlesW · · focus · HN ↗
Out of curiosity, have you come across Axiom (<a href="https://charleswiltgen.github.io/Axiom/" rel="nofollow">https://charleswiltgen.github.io/Axiom/) in your quest for more effective AI-assisted iOS coding?
rubing · · focus · HN ↗
[dead]
kulahan · · focus · HN ↗
truculent · · focus · HN ↗
kulahan · · focus · HN ↗
ricardobeat · · focus · HN ↗
ricardobeat · · focus · HN ↗
bityard · · focus · HN ↗
What harnesses do you recommend?
pkthunder · · focus · HN ↗
KnlnKS · · focus · HN ↗
pkthunder · · focus · HN ↗
lo5 · · focus · HN ↗
pkthunder · · focus · HN ↗
CharlesW · · focus · HN ↗
richardgill88 · · focus · HN ↗
Here's my minimal set up: <a href="https://github.com/richardgill/pi-extensions/blob/main/PI_SETUP.md" rel="nofollow">https://github.com/richardgill/pi-extensions/blob/main/PI_SE...
darkotic · · focus · HN ↗
sheepscreek · · focus · HN ↗
A framework/harness to develop capabilities such as OpenAI dot/Grok Bot. Can handle parallel conversations/forked conversations. But it doesn’t have to be user-facing at all.
It could be used to create an agent that sits inside your infrastructure - say constantly monitoring the firewall, taking actions autonomously (within hard guardrails I hope) and leaving an audit trail.
To be clear, they say nothing about guardrails or audit trails, it’s just how I would do build something like this.
sanex · · focus · HN ↗
ghm2180 · · focus · HN ↗
It addresses is a lot of pain points were built as internal tooling I maintained before this e.g. the need for a daemon for a number of good reasons e.g. executing/resuming a session from any machine, following conversations on my phone, having agents respond to comments on my CRM or asking interfacing it my homegrown PR review system. I can now have the harness run on that system and a durable pi session on a central server.
ofjcihen · · focus · HN ↗
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blahgeek · · focus · HN ↗
They explicitly said no MCP and no fullscreen TUI, which makes it minimal and attracts many people.
skohan · · focus · HN ↗
capocasa · · focus · HN ↗
shabbyrobe · · focus · HN ↗
The rationale for MCP and codemode I can swallow, Armin's writing on that makes a lot of sense, and meeting models where they are seems critical to me based on my own experience.
But for me, fullscreen mode is a _huge_ turn-off. I already have a backbuffer that I strongly prefer to use, it's called my terminal, and it's important to me. If the backbuffer-based version disappears, I'll be forced to migrate to something else (seems there are a few options here) or make my own tool, but that involves abandoning or porting my extensions, which turned out to be a huge superpower with Pi. Perhaps Pi Durable helps with that _and_ lets me keep my extensions, but I'd rather this was not necessary in the first place.
If switching to full-blown TUI has anything to do with how slow the "expand thinking" and "expand tool output" features get as the session gets longer, could that be mitigated by only expanding the _n_ most recent behind the default shortcut, and the slower "nah, I really do want you to expand them all thanks" can be a different shortcut?
If it's to add more fancy features that require fullscreen rendering and a dyed-in-the-wool terminal user like me might reasonably tolerate as a dismissable modal, make _those_ bits TUI, but keep the backbuffer in the terminal (for e.g. the session tree or the settings, those don't need to be in the terminal's scrollback).
And if it's for any other, richer interactions... can we just... not, instead, and let the terminal be the terminal rather than a single page web app?
badlogic · · focus · HN ↗
shabbyrobe · · focus · HN ↗
apatheticonion · · focus · HN ↗
I love alternatives to the big players but why is everything written in TypeScript or Python and takes up a gigabyte of ram.
I don't want to `npm install -g` something, just give me a single statically compiled binary that does the thing.
AI lowers the barrier of entry to Rust to virtually 0. As a side experiment, I have been rewriting Codex Desktop in Rust using native desktop APIs (gpui) and have made a cross platform copy that works on Windows, Linux, and MacOS. It runs at 120+fps and uses 40mb of ram. It's not that hard.
In a previous life, before the layoff times, I was working on a FaaS platform. If you need plugins, embed v8, quickjs or wasmtime/wasmer/etc.
People are acting like AI didn't eat up all the RAM on Earth. I had to sell my left kidney for the 8gb ram upgrade in my MacBook
bel8 · · focus · HN ↗
I find Typescript more approachable in many ways like compilation speed, extensibility, disk space used by cargo, LLM knowledge, and most devs I know already have node or bun installed anyway but not cargo, including me.
The speed in which pi can modify and extend itself is part of the appeal to me.
apatheticonion · · focus · HN ↗
This is more about demanding more of the big software vendors than it is about making an argument for the general software developer to write programs in Rust or Go.
We are talking about trillion dollar companies with highly paid engineers and unlimited token budgets.
As someone who has been writing TypeScript since the beta and started writing Rust professionally only 5 years ago, I'm about as productive in Rust as I am in TypeScript - so if I were distributing software, I'd want to ensure the end user has the best possible experience and that's hard to achieve with the node/python ecosystem.
"Run this bash script to install my CLI tool" behind the scenes it downloads a full copy of Node.js, installs the npm dependencies, add executable scripts for the entry points, updates PATH. It takes almost a second to start up, has no threads and uses way more memory than is necessary. Extend that to Electron applications which not only bundle Chromium, but also bundle Node.js - that's two v8 engines running and a process that starts with a memory footprint of almost a gigabyte.
Compare that to just downloading a portable self-contained single executable and running it.
The end user is not installing cargo, compiling, or anything - they just run the binary.
bel8 · · focus · HN ↗
It's minimal and intended to be modified.
apatheticonion · · focus · HN ↗
When was the last time you patched Pi / OpenCode / Claude dist or source code before running it?
Most people use plugins, and native apps have no issues with that.
bel8 · · focus · HN ↗
Funny you ask. Yesterday I patched opencode to replace \ paths with / depending on some heuristics. Couldn't get a plugin to fix in all cases I needed. Solved in one minute :)
And plugins for executables just suck compared to "just create a .ts file in this directory and edit/test it in a few seconds until satisfied".
apatheticonion · · focus · HN ↗
Only if you wanted to write them in Rust, I guess? You could also write them in Go, TypeScript, Python, whatever.
Plugins don't need to be in the host language. It's up to the harness writer to ensure the plugin system makes sense for the patterns of plugin writers.
Then it's up to plugin writers to ensure their plugins are performant so people like using them.
> And plugins for executables suck compared to "just create a .ts file in this directory and edit/test it in a few seconds until satisfied".
Not really? Deno, Node.js are both embeddable within a native application, so plugins can be written in TypeScript without any change in expectations from the plugin dev's perspective. There's also QuickJS and LLRT which use like 1000x less resources than v8 (faster for plugins, slower for servers).
No one is asking plugin devs to change, just that the harness writers provide better platforms to build on top of
bel8 · · focus · HN ↗
You get the worst of both worlds and that's probably why the most harnesses tools don't do that.
What you're describin already exist but the target audience for such is small. I invite you to try and watch the adoption :) It's just a prompt away.
apatheticonion · · focus · HN ↗
I'm not sure what you're arguing for? Are you saying that you think it's acceptable that that multi-billion dollar companies with strong engineers and unlimited token budgets ship low effort products that waste the limited resources available on consumer devices?
Like, if Pi/Claude/Codex/etc used a fraction of the resources and your experience as a developer or plugin developer was unchanged - you're opposed to that?
> I invite you to try and watch the adoption :) It's just a prompt away.
I am actually writing a native harness that is a pixel perfect clone of the Codex Desktop harness haha. I expect no one to use it because adoption is not about quality, it's about marketing and that is dominated by a handful of players.
That's not going to stop me because I'm doing it for fun, but if I can do it with a handful of DeepSeek tokens and a few weekends - there's no excuse for the big players not to.
bel8 · · focus · HN ↗
Alright if you believe this then we are wasting our time arguing pros and cons of using different technologies.
I'm happy you're creating your own harness. I plan to do that too if pi gets in my way but it is so small and flexible that this has not been the case yet.
Bluestein · · focus · HN ↗
I am really hoping a combination of the RAM-pocalypse and AI coding will result in less bloat. At some point ...
joshAg · · focus · HN ↗
Same reason everything's an electron app now. First mover matters to the makers and to the consumers more than performance and attention to those details.
schlarpc · · focus · HN ↗
jacquesm · · focus · HN ↗
solarkraft · · focus · HN ↗
Not really. It lowers it, sure. By a lot even. But you still have the system requirement for compilation and ecosystem to deal with.
redrix · · focus · HN ↗
[0]: <a href="https://earendil.com/posts/pi-durable/" rel="nofollow">https://earendil.com/posts/pi-durable/
geauxvirtual · · focus · HN ↗
And when a Linux distro bumps a dependency that Node requires on without updating Node to use the updated dependency, then Pi doesn't start.
capocasa · · focus · HN ↗
<a href="https://3code.capocasa.dev" rel="nofollow">https://3code.capocasa.dev
Written in Nim. Unixy scrollback but cross plaform. Tested for token efficiency.
rylando · · focus · HN ↗
jrmeyer2 · · focus · HN ↗
gjm11 · · focus · HN ↗
nicce · · focus · HN ↗
I think they mean that most companies that use these Tolkien names, are on the dark side.
markerz · · focus · HN ↗
dmazin · · focus · HN ↗
TZubiri · · focus · HN ↗
newswasboring · · focus · HN ↗
TZubiri · · focus · HN ↗
newswasboring · · focus · HN ↗
Are you sure about that? All llm use is like this?
TZubiri · · focus · HN ↗
newswasboring · · focus · HN ↗
gholap · · focus · HN ↗
> When I'm old I want people to remember Tolkien named companies for things other than weapon and surveillance systems.
Source: <a href="https://x.com/mitsuhiko/status/2041855748481695774" rel="nofollow">https://x.com/mitsuhiko/status/2041855748481695774
v3gas · · focus · HN ↗
gholap · · focus · HN ↗
Yizahi · · focus · HN ↗
lucas_t_a · · focus · HN ↗
twobrainy · · focus · HN ↗
yencabulator · · focus · HN ↗
kergonath · · focus · HN ↗
Though I find it funny that they put “Bearer of Light” as a description, at least on their GitHub page. AFAIK Tolkien did not used the phrase, it is maybe a bit too close to the Latin version, Lucifer. Talk about a thing corrupted by darkness.
amelius · · focus · HN ↗
wongarsu · · focus · HN ↗
Or maybe from the 9th century poem Christ I [2], which translated to modern English starts off with the words
IKEA catalogs using Swedish names, and Swedish being a Germanic language that stayed truer to its Germanic roots than English did, it's not that far off. In a weird way1: <a href="https://en.wikipedia.org/wiki/Aurvandill" rel="nofollow">https://en.wikipedia.org/wiki/Aurvandill
2: <a href="https://en.wikipedia.org/wiki/Christ_I" rel="nofollow">https://en.wikipedia.org/wiki/Christ_I
imagetic · · focus · HN ↗
ttmacer · · focus · HN ↗
Since January I use Pi professionally as well as personally and I can only recommend to start small and grow your harness over time. For example, for an agent in production it was so helpful for me to use Pi in interactive mode via tmux to get a feel of the agentic flow, tool calls and reasoning traces for a certain use case while only the stylized responses are rendered in Telegram via an extension to the user. As a Developer, I have full technical observability and control while providing and incrementally improving a service to a user at the same time.
Excited how Pi Durable will fit in and can support more. Congrats and thank you!
asp_hornet · · focus · HN ↗
ttmacer · · focus · HN ↗
ghm2180 · · focus · HN ↗
The second case, more recent, is one where I use actively now is linking pi sessions to some artifact like a code change(PR or diff) or a collection of document and then continuing the session in that context.
phkx · · focus · HN ↗
jkl5xx · · focus · HN ↗
nibbleyou · · focus · HN ↗
ttmacer · · focus · HN ↗
In the past I used this abstraction conveniently to setup different agents for different purposes. I kinda like having this abstraction on my filesystem to inspect instead of it being hidden away in a opaque harness or, even worse, the weights of the model.
GreenWatermelon · · focus · HN ↗
codybontecou · · focus · HN ↗
ttmacer · · focus · HN ↗
zmmmmm · · focus · HN ↗
I don't mind though, because I think either way it leads to a better design under the hood when things are built to be modular.
ecocentrik · · focus · HN ↗
redmalang · · focus · HN ↗
Slopsite here: <a href="https://piproxy.latchlabs.dev" rel="nofollow">https://piproxy.latchlabs.dev
iluvcommunism · · focus · HN ↗
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imagetic · · focus · HN ↗
blinded · · focus · HN ↗
kimseungyong · · focus · HN ↗
I'm working with Claude's workflow, but I haven't yet felt any demand for customization.
For those who use this well, could you share examples of how you use it?
puilp0502 · · focus · HN ↗
warmwaffles · · focus · HN ↗
capocasa · · focus · HN ↗
SkillKeeper · · focus · HN ↗
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nixpulvis · · focus · HN ↗
fishfasell · · focus · HN ↗
jupp0r · · focus · HN ↗
nixpulvis · · focus · HN ↗
I've been assuming a harness is basically a set of tools and a TUI for passing text to the model and the model coming back with tool calls and user responses.
Are the tools really that complex and different between harnesses?
Pxtl · · focus · HN ↗
nixpulvis · · focus · HN ↗
- read - write - edit - bash
Pxtl · · focus · HN ↗
nixpulvis · · focus · HN ↗
Seems to support my skepticism.
capocasa · · focus · HN ↗
Each family gets their own system prompt, based on the original harness one, but compacted and includes instructions for more brevity.
shpx · · focus · HN ↗
octoberfranklin · · focus · HN ↗
Man, first MCP then this? The main reason I use Pi is because it didn't try to reinvent my terminal's buttery-smooth native scrolling -- something no terminal client can ever match.
Did you all get acquired by private equity or something? The enshittification is coming at us fast.
tesnorindian · · focus · HN ↗
by2kaapi · · focus · HN ↗
But loved the minimalism, extensibility! It's a very capable harness.
Have my own extensions for MCP, subagents, ui, history management etc. overall i feel my workflow has got a lot better.
Love pi!
OtherShrezzing · · focus · HN ↗
slekker · · focus · HN ↗
dracotomes · · focus · HN ↗
worldsayshi · · focus · HN ↗
outadoc · · focus · HN ↗
crazeddog · · focus · HN ↗
TL;DR: Pi is amazing.
lionkor · · focus · HN ↗
I run it like `sbh --net pi` or `sbh --net --docker pi` depending if I want the agent to have docker access.
sbh: <a href="https://github.com/lionkor/sbh" rel="nofollow">https://github.com/lionkor/sbh
sid_talks · · focus · HN ↗
Is it worthwhile to spend time and effort into setting up and switching to Pi? I always see people praising Pi online but I am curious to know from people who switched over from OpenCode why they did so and what I am missing.
vincent-uden · · focus · HN ↗
luijk · · focus · HN ↗
vincent-uden · · focus · HN ↗
ropintus · · focus · HN ↗
manmal · · focus · HN ↗
eloisant · · focus · HN ↗
What's great with Pi is that it's very easy to extend, because it knows its own doc. So you tell it "implement a plugin that does this" and it does it directly in its own folder.
That means I have a plan mode that works exactly the way I want, I have a hook that cleans up added comments after each change, I can ask "pull this github PR and assess the comments", etc.
Mashimo · · focus · HN ↗
Same with opencode, no? It has a default skill just for that.
weitendorf · · focus · HN ↗
I've been avoiding investing in these kinds of tools and workflows partially because I don't understand the UX (and partially because I worry UX and tooling will change so fast that I won't get a positive ROI). Your hook sounds like a script, but your plan mode sounds like an interactive TUI, and "pull this PR and assess" sounds like a reverse proxy tool or something?
I can definitely see why the custom plan mode is useful vs just calling a script or asking the model to do something, but what's the draw to building comment cleanup and github API access into the harness vs running the comment cleanup as part of CI, or just asking the model to pull a PR and review it using gh/the web UI/the github api (with no special harness handling)? Does the model get updated with changes you make to files it already read or recently wrote?
The way I normally use coding agents is by giving them a very large task specification in a fresh session with some kind of verifiable exit criteria, and sending them off + staying out of their way. Normally I would just use other sessions or run scripts to do these things because the coding agents I've used queue any /command I give them (very frustrating when you have to wait 30+m just to check usage!) while the model is working, and in my sessions the model is working >90% of the time, so I usually have other terminal windows or applications open anyway.
rbanffy · · focus · HN ↗
robertlagrant · · focus · HN ↗
jasonhkl_03 · · focus · HN ↗
holoduke · · focus · HN ↗
skapadia · · focus · HN ↗
claud_ia · · focus · HN ↗
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andai · · focus · HN ↗
<a href="https://departuremono.com/" rel="nofollow">https://departuremono.com/
Jeeetendra · · focus · HN ↗
julesrms · · focus · HN ↗
Like Pi, it's plugins all the way down, provider-agnostic, minimal system prompts, threaded sub-agents, code-mode, multi-client remote sessions, worktrees, a context window you can actually see and edit, etc etc
Where Pi is way ahead is the plugin ecosystem, and that takes people, which is hard to get amid the current deluge of agent action. So if there's any spare oxygen trailing off this thread, I'd love any Pi-heads who fancy a bit of GUI action to come and kick the tyres..
fatata123 · · focus · HN ↗
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vorticalbox · · focus · HN ↗
It’s great that’s plugins all the way down the issue I find is I haven’t missed anything enough to need a plugin.
jonenst · · focus · HN ↗
KolmogorovComp · · focus · HN ↗
jon23d · · focus · HN ↗
julesrms · · focus · HN ↗
kraktoos · · focus · HN ↗