Have been reading the book: The Wise Heart by Dr Jack Kornfield.
Profound and inspiring. Highly recommend.
Any conversation
Really glad to be using Haskell for work - especially in today's climate with agentic coding.
Our team uses containers to keep our development environment consistent across team members, though, and most agent sandbox approaches want to either offload your work fully to the cloud or they want to sandbox the agent harness process itself.
We're not ready for full cloud based development (yet?) and sandboxing just the agent doesn't work for us when the agent needs to run docker.
... because letting the agent run docker gives them a too-easy escape hatch from their sandbox.
So we're currently stuck with using VMs. This turns out to be tricky but seems do-able.
My current approach is to provision a VM image and use Incus for the execution. My main goal is to keep my current workflow of local/non-agent dev working seamlessly and share the source with the VM/agent.
This means sharing my working dirs with the agent VM but overlaying artifact dirs from VM-owned block devices so we don't take too big of an IO perf hit.
I also don't want the agent to be able to
git push so that means we need some quirky git config to rewrite origin paths and thread through some agent specific PATs ("thanks" GitHub) for read-only repo access. These ALSO need to be threaded through to the development containers - they need to clone private repos.... in the end, this seems to work but I haven't lived with it for long.
There are still some quality of life issues to work out, but I think it'll work out.
At this point, I've removed all coding agents from my host - and that's nice.
Curious, why does using Haskell make a difference here?
It's tangential to the sandboxing topic, really. I started the first post with a broader intent in mind and then elaborated on the sandboxing setup I'm working on.
For AI-assisted coding, though, it's nice because Haskell provides a lot of feedback earlier in the development process compared to lots of other languages. It tends to work once it compiles (obviously not all the time).
oké, megdumáltatok, a héten telepítem a kis virtuális állatseregletem mellé (webszerver, mechanikus 1. generációs robotkezdemény, led kijelző szalag) az első ai agent chatbotomat, egyelőre Virtualbox Ubuntu alá
Okay, you've got me, this week I'm installing my first AI agent chatbot next to my little virtual animal herd (web server, mechanical 1st generation robot initiative, LED display strip), for now under Virtualbox Ubuntu
az interneten nem lehet egy képet sem átméretezni, sem Windows alatt, a Grok is csak hozzávetőlegesen dolgozik, mi következik ebből, muszáj lesz beengedni Gemmát, mintha Linus Thorvalds a napokban panaszkodott volna, hogy a Linuxot is elárasztotta az ai
You can't resize an image on the internet, not even under Windows, Grok only works roughly, what follows from this, we'll have to let Gemma in, as if Linus Thorvalds had complained the other day that Linux was also flooded with AI
signals. thinking about shifting my mental framework to identify signals instead of waiting for concepts to be assembled. exploring the amount of energy and opportunities for distractions through the operations of processing what just happened and what is happening to short circuit latent and unnecessary systems. cut through the assembly processes and identify the raw signals. recognizing that naming these "raw signals" is misleading. maybe, shifting observability lower in the stack.
