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Posted by niemandhier 16 hours ago

OpenShell – A safe, private runtime for fleets of autonomous AI agents(github.com)
397 points | 194 commentspage 5
minzf581 6 hours ago|
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prompter_note 7 hours ago||
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byoungyoung 13 hours ago||
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150g2 15 hours ago||
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iluvcommunism 14 hours ago||
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moooff 15 hours ago||
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bredren 14 hours ago|
Sounds interesting. Can you provide some examples of stuff you've used it on?
moooff 14 hours ago||
I was using it in an air gapped environment vs a local inference engine running a qwen-coder-next. Installtion of harnesses on the machine and other things were ruled out because of security constraints.

There i used it to analyze an old visual basic application which creates custom pdf files. it worked surprisingly well. it took some rounds but in the end it got all requirements and scaffolded me a skeleton for a python rewrite as a web-application. Then i worked from there with it to get a prototype.

LostBeard 13 hours ago||
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flohofwoe 14 hours ago||
From the top of AGENTS.md:

> We design systems and use agents to implement them — this is not vibe coding.

Lol, what is even the point of such a statement, and who are they to define what vibe codig is or isn't :D

tomsmeding 14 hours ago|
If it's in AGENTS.md, it's not a statement for a human, but for the LLM. Who knows, maybe they have seen, or think to have seen and now cargo-cult, some behaviour improvement due to the sentence.
flohofwoe 14 hours ago||
So a similar shibboleth as "You are a highly experienced software engineer..."? I really wonder if that ever made a difference (or even degrades quality, because people who advertise themselves on the internet as 'highly experienced' are quite often snake oil salesmen ;)
RevEng 6 hours ago|||
Yes it did help, at least back in the day when they weren't doing tons of RL. If you just train on random text, your prior probability is to return the average of everything. Ask for software, get average software, or worse yet, randomly get either gold or shit. By adding constraints to your prompt like "you are an experienced engineer" it will prefer to return answers like an experienced engineer would give and less like a random noob would. It doesn't suddenly make it smart if it never was, but it helps to reduce the variance and bias towards the good outcomes.
calgoo 13 hours ago|||
I still use use `Please` a lot when making requests from LLM based on the old idea that people that where polite on stack overflow tended to have better answers :D

However, these days i think i do so because of how much i write for LLMs, and dont want to start sending emails to humans without proper etiquette.

sscaryterry 15 hours ago||
> OpenShell collects anonymous telemetry

Spyware

roosterIllusi0n 15 hours ago|
Use local ai to find any possible telemetry and disable it in the code. Run your own local git repo to hold local edits so you can update and retain them.
greenpizza13 13 hours ago||
You don’t have to disable it in code. Scroll up in this thread to find the officially support env vars.
thway15269037 8 hours ago||
You can never know for sure that they haven't conveniently forgot to cover with if(env) one or two of twenty two exfiltration functions. I'm not claiming they did that, but I've seen that already.
smashed 15 hours ago|
Well, I guess its time to shamelessly plug my agent sandbox, egzo.ai [1]

Looking at the complexity of OpenShell and the simplicity of just building on top of docker, in a whitelist only mode.. I don't quite get the use-case of OpenShell. May be for large orgs where there is so much legacy and difficulty in organizing access to tools, OpenShell can simply re-use whatever you already have access to on your corporate account.

I chose to build straight on top of docker and agents are simply fully sandboxed by default. All data and network access must be granted in a simple project file, docker-compose style.

The web-ui connects to the docker socket and lets you spawn agents, and connect terminals. I'm having lots of fun with it and it allows me to cleanly organize and isolate my projects.

End-goal is to monitor for the Lethal Trifecta [2], ensuring all individual agents are properly isolated. Not quite there yet.

1: https://github.com/egzo-ai/egzo 2: https://simonwillison.net/2025/Jun/16/the-lethal-trifecta/