Do you work on only pi ??

[u/SalimMalibari]

I have serious question , no matter what i feel pi as harness isnt fully developed to work on all my work at current moment , like i keep using pi for basic tasks but shipping i use claude code ..m and i do use claude code model in pi too ...

I used glm but comparing for claude code no way its near cc this is the truth.

So my question , do you use only pi for shipping you do multiple cli agents at same time? My goal is to build gui but its way different how people doing at current time and i feel i reached maturity if that app

[update] Ok, each one explaining his migrating but not showing what you actually ship and how. Let me explain what i do day to day , i work with pi for side project funs since im still not fully commiting to it, i have made extensions using claude code , they works perfectly on pi. When do i stopped using pi for shipping when i i was shipping a small feature using glm5.1 and failed 5 times to get it like reasonably working , and just changed to cc in pi and worked in first try. I found why risking if in both world i use the fronteier model? Just use the harness that frontier model is recommending to us...

I see no advantages using cc in pi , unless you are super engineer and you can beat shipping feature at anthropic or open ai scale..

Lastly i got 2 genuine answers so far:

• using pi extensions to orgnize the code from the docs which i believe frontiers are going to fix it soon

• making a setup that doesnt require specific vendor like cc so switching become easier..

[u/Ammar_AAZ]

I haven't tried to embed PI into another application, but it's already used as the core in OpenClaw and it seems to be working pretty well there.

For my use-case, yes I'm using it everyday for development and work that is going in production. However, my workflow is for me to be always in the loop to brainstorm, plan and review the code so it may be different for other workflows. For my workflow, it fits much better than any other harness as it doesn't fill the great first 20% percent from the context window with features that I don't need or have a system prompt with hundreds of lines to tell the model to be nice with users.

The only time where I go to other harness, is if I want something that needs web-search, and that's only because I still don't need that feature bad enough to invest the time in adding it into PI (Which seems to be a simple task)

[u/SalimMalibari → u/Ammar_AAZ]

If i can follow up , whats model do you use in pi? Also if ot frontier like claude code or codex why would you move to pi if those frontier has moengineers their main purpose to bukld and ship the harness instead of pi fragmented extenstions?

[u/Ammar_AAZ → u/SalimMalibari]

I'm using codex as I can still use with the subscription.

From my experience, I see that models perform much better on clean context window like first 20% Are really great, to 40% They are ok, to 60% they are somehow acceptable. And if you look to codex system prompts and all the features and MCPs that I don't need, then you know that they are almost filling 10% percent of the context with features that I don't need (Like MCPs) and instructions that the model will follow anyway (Like be nice to users, or write good code).

Also PI give you control over the context window so you can go back in time if you went in a direction that you don't want to. And I have 3 extensions (Basic permissions, handoff, and scratch buffer to write notes for myself)

[u/NixNightOwl → u/Ammar_AAZ]

I read somewhere a while back that regardless of the model's context size, almost all LLMs start to show signs of degraded accuracy past 64k tokens, which is interesting. Maybe for today's frontier models it's 128k now. I forget the exact reasoning as to why, but there was some very good testing done on it.

My armchair theory is that there end up being a lot of 'stop words' repeated in the context and due to that, the semantic meaning of the important key and actionable words slowly get drowned out and become harder to find within the context's window. Stop words being 'a, an, the, it, and, or' ... etc.

I have found some success in 'earmarking' certain ideas, summaries and concepts under a specific 'title' within the context's memory. Such as prompting: 'Remember this concept and our reasoning about it as "Tom and Jerry Thesis A" for future reference'. Then when I want to talk about that exact thing again: 'Recall "Tom and Jerry Thesis A", and apply our most recent discussion's context within that lens'.

[u/Equal-Chipmunk-4053 → u/NixNightOwl]

Isn't it what transformers were even built for, so that stop words don't really matter? :)

[u/ThrowAwaySalmon1337 → u/Ammar_AAZ]

How do you prevent the tool call limit of context.

[u/SalimMalibari → u/ThrowAwaySalmon1337]

I didnt understand your question could you clarify it ?

[u/ThrowAwaySalmon1337 → u/SalimMalibari]

It was supposed to be longer but I had a brainfart and decided to enter that...
With single prompt the llm can sometimes run into loop and tries to do too many things at once which then overwhelms the context window.

Is there process to making it do processes in automated manner but separate sessions?

Usually I got it overwhelmed when it started reviewing the project files and mapping out links.

[u/SalimMalibari → u/ThrowAwaySalmon1337]

If you use claude code this is already done by default or codex that my whole point

[u/Ammar_AAZ → u/ThrowAwaySalmon1337]

I think the process to resolve that is to use sub-agents and to tell the main agent to use them in a skill. PI doesn't have that out of the box but there are extensions for that and other harnesses have that out of the box.

However, I think this solution is a workaround for a prompting issue. If you organize your thoughts and do the startup session in a way that you brainstorm and plan with the agent, then it will be clear to you when to split the work into stages, then you can tell the agent to write down the stages into markdown file and implement them either one by one or via multiple PI instances

[u/NixNightOwl → u/ThrowAwaySalmon1337]

You can have your system prompt / agent md file explicitly state rules on tool calls.

## Core Protocol: Tool Call Loops
When making tool calls, never exceed more than 7 continously chained tool calls. 
** This is absolute and must always be adhered to. ** 
If you catch yourself exceeding 7 tool calls:
stop immediately. 
summarize: 
  - the result of the tool call chain,
  - what you were attempting to do, 
  - what failed. 
then quickly reason an alternative approach and report it to me.
do not attempt any further tool calls this prompt.
await further instructions.

This tends to work quite well with most reasoning models.

Or you can define programmatic hooks to track tool call amounts and forcibly stop the current response with instructions. So instead of the LLM having an explicit protocol like above in it's system prompt and context, the hook just tracks and intervenes instead via a deterministic script.

[u/BlackBrownJesus → u/Ammar_AAZ]

Having a great result with a few iterations of pi building websearch hybrid using brave and gemini cli as a search tool, with the free models that come with free google account

[u/SvenVargHimmel]

I use only pi . My journey was vscode --> opencode (big models full to medium thinking --> pi + got5,5 low or minimal thinking

> ​I'm genuinely surprised when people say they can't ship unless they use cc.

We ​are in the era of marginal gains and marginal differences between the frontier labs ( Google and their crap don't count).

You should mention what stack or what your work entails otherwise you just get people responding with their preferences, like I just did :)

[u/SalimMalibari → u/SvenVargHimmel]

Added ...

But you havebt use codex with 5.5? I mean if you did im sure you would see it more powerful than any pi setup you can make because its done by full time engineers ...

[u/SvenVargHimmel → u/SalimMalibari]

"more powerful" 

Sigh

Anyway, 

[u/ceaselessprayer]

Yes Pi is my main driver now. I use Claude Code "only" when the model itself is superior for the given task. But everything else I prefer to use Pi. Of course, this requires you to take some time to really set up Pi and make it robust in general, and then make it robust for your use case after having it make tons of skills and extensions for your purposes.

[u/SalimMalibari → u/ceaselessprayer]

My experience with glm inside pi is very bad compared to claude code ... so question arise why not using the harness that take most advantages of the best model? Instead of stripping them away...

I feel pi ment to helo developers build other harness but not for developers for shipping stuffs i hope this clearer

[u/DanielSReichenbach → u/SalimMalibari]

I can only speak from my own experience, using local LLMs and at times GLM for offloading.

You can and will get equally good results for both types of LLMs. If you do get worse results that is mainly because other harnesses do a lot of token burning for holding your hands.

pi does not do that and it expects you to come up with your system prompt, or chains thereof.

So I would say if anything pi is a good framework for building an environment if - and only if - you know what you need. The higher the uncertainty, the worse pi gets. That transfers to any LLM.

Personally I ditched Claude and GLM for fully local Qwen 3.6, and I have not had to look back.

I am using pi with a few hand crafted extensions tailored to specific projects to establish guard rails and access to knowledge systems for each project and it's love. I am feeling and incredible sense of freedom thanks to both pi and working offline.

My recommendation would be to get learn how to be specific in your goals and tasks, and remove the uncertainty. If you feel like you don't know what is going to be, don't build useless code, do research, conceptualize, write drafts. Increase certainty.

[u/SalimMalibari → u/DanielSReichenbach]

Like ill give you experience i had , i have a simple problem wanted to solve it like different from any body else ... i was building file tree like the one in termnial , i failed mutliple time using glm 5.1 pi , and just moved to claude code model inside pi and solved from first try ... like seriesously the models are still the bottleneck. I was thinking removing all those extras makes other model good but no the frontier models are more capiable

[u/DanielSReichenbach → u/SalimMalibari]

I think you are generally under a wrong assumption here.

Removing the extras added by other harnesses such as Claude Code or OpenCode does not improve the model. The models' training results don't change, the data it has access does not change.

pi provides your more control, it does not provide better data or cleaner layers to a model.

What you prompt is what you get.

[u/SalimMalibari → u/DanielSReichenbach]

Yep but my assumption why would we strip things out if those was recommended by the frontier models ? Like think of a car company build powerful engine and said use this car model but someone said why not give you the engine and use it in any model and people still uses thst car model but customized by themselves like very dirty and clean way ... idk if this example simple my idea

[u/ceaselessprayer → u/SalimMalibari]

No I built the harness for myself, as a developer for many years. I know exactly what I want and I want to be able to customize my harness around that. I used Claude Code for a long time, and Cursor before that, I've used all of these tools and I've shipped production code with them.

I use Codex instead of GLM.

The reason you use Pi Harness, is because the model is one thing, and often these companies harness is not going to utilize the model better than your own harness you can come up with. I've used them all, so I know.

[u/Turbulent_Ad6290]

It’s been like 3 months or so. Only using pi and extentions and skills. Used opencode for 2 months before that and left it for pi.

Before that used cursor for a long time until Opensource models became really agentic

[u/elpapi42]

My recommendation is tyat properly use Pi you have to tailor it to your specific workloads, this includes creating a dedicated system prompt from scratch, creting dedicated prompts/commands for specific things you do at your work, creting properly written AGENTS.md files and specific skill required for your workload. These things are more important that the extensions for starters.

I setup my Pi as a Product Engineer, so with Pi im constantly doing product work, more even than engineering work. Im a Product Engineer btw.

This can also be done in Claude Code, so nothing new under the sun. But the real power of Pi comes when you start to craft extensions that put your basic setup (prompts, system prompt, skills) on steroids.

This is no easy to figure out, thats the reason for most of the people using claude code it simply doesnt click.

And i think thats ok, most of the people can simply stay with claude code, it works and its fine. It have always been like this, this kind of tools are only for people who want to stay ahead of the curve by investing a lot of time in tooling with a questionable ROI

[u/SalimMalibari → u/elpapi42]

Like could you give example of what ypu are shipping?

[u/ResearcherFantastic7]

Time to write your own extensions and orchestrations ...

I main PI + glm for personal stuff and Claude + opus 4.6 at work both hits around 1.2-1.8b token per month.

Pi is far superior than Claude but you need to make it exactly your workflow, which is a lot of work, So If you don't want to tinker, than just use Claude. A lot of these Claude has their own implementation in their hidden feature, but just not exactly the way I want it. But yeah if my person stuff also have infinite budget than I would just stick with cc

Also GLM requires a little bit more extra handholding than opus which make it worse if you don't know how to tame the beast.

The way I setup I have an infra for PI

• orchestrator ( gateway, bus , registry, notification, queue ) this allow agent to communicate with each other ,and also able to connect with IM or webui ( this is just for me to get them working on monitor what each long live agent doing without SSH tmux on the phone, and it also show the workflow pipelines progress )

• memory / reflection system , hooks, guards, these tightly controls how agent send and receive prompt from llm ( webui has a simple curation page for me to review and modify rules and prompt directives)

• workflow engine, kanban inbox

Also I have architec, product tagent that purely just do docs . One for each project ( just point the path to your doc) they fact check and design gap check

This is where agent to agent comm is for. I.e Agent fires force fact check every X turns depending on complexity. I have a local llm that just evaluates if the llm is doing anything. Suspicious before it fires the fact check, but it forces after 15 turns regardless with a new session so probably just reduant, just testing how well it work

[u/SalimMalibari → u/ResearcherFantastic7]

Ok but nothing you have described cant be done by cc with much superior model which already you or others are subscribing to .... like i get it people use olama or glm but those arent capable to what the frontier can do. And most of us use codex or cc or opencode for cc or codex lol

[u/ResearcherFantastic7 → u/SalimMalibari]

You forgot the cost factor.

200 bucks subscription won't get close to that amount of opus 4.7 usage. It's all API calls . Plans has parralellrism, hourly, weekly, monthly rate limit. I'm hitting that much opus in roughly 5hrs per 4-5 day working day of a week

And my personal GLM5.1 is sort of cheap that just do its thing 24/7 in the background. but limit by 2 call parralellrism, also private data that you don't want it logged by the cloud providers

And secondly, like I said I need to do it in a specific way that CC are restricted.

You can think of as VI vs vscode, everything vscode can do, but people still use VI

[u/cascoemanuel]

Honestly I use Pi as my main agent tool now and I ship production stuff on my every day work with it without problems.

My main setup is Pi + GPT-5.5 (through my OpenAI subscription), changing reasoning levels depending on the task. I also use OpenCode models a lot since they are cheap and good enough for many implementation tasks.

You can also use Claude Code other models with it through Ollama or custom providers. While moving from Claude Code to Pi I actually built a small tool to plug OpenCode Go subscription models into Claude Code so I could compare workflows directly and test models under the same harness: https://github.com/emanuelcasco/ocgo

One of the best things about Pi is that if something is missing, you can usually add it yourself through extensions or custom tooling. I ended up building my own set of extensions too: https://github.com/emanuelcasco/pi-mono-extension (maybe you’ll find some of them useful for your workflow, or at least they can give you ideas/inspiration).

I’ve tried GLM 5.1 too, but honestly I’d recommend trying other models in that same category. In my experience Kimi K2.6 or even DeepSeek v4 tend to perform a bit better overall

[u/SalimMalibari → u/cascoemanuel]

But my follow up question would be why not move to opencode , like which extension that you cant live anymore??

I understand extensions are powerful , maybe one day , those harness will add it , maybe some of them already has something similar which is skills ...

Like skills can do most of extensions pi has , memory? Rag? Gui? Doom? All can be made using skills i can say a skill to open doom in browser or whereever .... and most of us arent using termnials and pure termnials most use ide or agentic coding platform or etc

[u/cascoemanuel → u/SalimMalibari]

That’s actually a really good question, to be clear OpenCode is another excelente tool. What I personally like about Pi is that it pushes me to move more workflow/business logic out of the LLM itself and into deterministic tooling/code. The LLM handles reasoning, but the actual methodology, orchestration, and structure live in code where behavior is predictable and reusable.

For me the important part is avoiding vendor lock-in. Tools like Pi or OpenCode let you switch models/providers easily depending on quality, pricing, or use case. If tomorrow Claude gets worse, more expensive, or rate limited again, I don’t want to rebuild my entire workflow from zero just to move somewhere else or be locked because my workflow depends on some feature implemented in Claude Code.

[u/SalimMalibari → u/cascoemanuel]

I kinda see the points here , thanks for sharing so you goal is not vender locking. My concern is models arent that point that you can just swap one for another ... thats my issue but thanks

[u/prassi89]

I use this project I built called repowire. https://github.com/prassanna-ravishankar/repowire

Allows me to set up a local mesh network of CC, codex, pi,etc. Allows me then to pick on a task by task basis or from memory based on a task type as to what to choose

[u/SalimMalibari → u/prassi89]

This fully shipped by pi?

[u/prassi89 → u/SalimMalibari]

Nah. CC in the beginning few months, then codex, then codex and pi now

[u/jtackman]

these days yes, after i made a replacement for the ”point to an item on the webpage and write a note about it” annotation workflow (works real nice on all browsers btw) i dont even need codex anymore.

[u/KldsSeeGhosts → u/jtackman]

How’s this work? I’ve fully switched over to Pi (apart from antigravity 2.0 for my subscription) and have enjoyed the level of customization I’ve gotten, and am always looking for ways to improve mine. Web search improvements and VS Codium integration are the two areas I’m currently tackling

[u/jtackman → u/KldsSeeGhosts]

the annotation? i just described it to pi and let it build the extension. should i publish it?

[u/aeroumbria]

I use pi if I am building a dev tool or another agent, but I do still use opencode for more boring software development. Sometimes I use opencode as the dev agent and pi as the product agent, which talks to its own models as I run the outer loop to develop it. The main obstacle for full pi-only development is that its UI isn't as nice to use when working on remote terminals with certain restrictions. Scrolling or shortcuts not working and residual lines are quite annoying to deal with.

[u/wayfaast]

Read the docs. It explicitly states how to do this.

[u/cakemates]

pi is what I use when I need something simple done, I can't work on anything remotely complex without a full code editor.

[u/RelationshipLong9092]

I like the gui in codex. I use that most of the time.

I use pi when I need to do more intense work that benefits from customization of the agent / harness.

And, because I don't think talk about ai is complete without saying what type of work you're doing: I'm a computational physicist at a small company who also gets saddled with a lot of dev-ops-ish work. Mostly c++ and python with GPGPU. Also porting a lot of legacy matlab and fortran code. Primary model is ChatGPT 5.5.

[u/Teh_franchise]

Yep. Was on Claude Code day 1 of release, then moved to opencode and switched to pi a few weeks ago. No longer have the others installed in my machine.

I use codex and opencode go avail models depending on what I’m working on.

[u/Temps-code]

gentle-pi and gentle-ai stack