Congratulations on the !
Any conversation
โโโโโโโโโโโโโโโโโโโโ โโโโโโโโโโโโ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โโโ โโโโโโ โโโโโโ โโโ
โโโ โโโโโโ โโโโโโ โโโ
โโโ โโโโโโโโโโโโ โโโ โโโ
โโโ โโโโโโโโโโโ โโโ โโโ
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).
szรณval technikailag nem adatkรถzpontnak neveznรฉm a fลterminรกlt, hanem maximum vallatรณszobรกnak MI รผgynรถkรถk rรฉszรฉre, jelenleg el vagyok akadva a Windows 11 telepรญtรฉsnรฉl, รฉs nรฉhรกny kรถnyvet รฉs scriptet mรฉg lementenรฉk rรณla รบgy biztonsรกgilag, mielลtt belefognรฉk a vallatรณszoba kialakรญtรกsรกba, itt tรฉnyleg olyan sandbox van, amibลl nincs nagyon merre mรกszkรกlni, kivรฉve, ha direkt kikรผldรถm valamelyik webes alkalmazรกsra
So technically I wouldn't call the main terminal a data center, but more of an interrogation room for MI agents. I'm currently stuck installing Windows 11, and I'd like to download some books and scripts just to be safe before I start building the interrogation room. It's really a sandbox here, with nowhere to go except if I send it directly to a web application.
I've been building a Markdown variant called Zd that's focused on extensibility and simplicity. I'm curious what you would change about Markdown if you were designing it from scratch, what challenges you face as a user, or what you wish were easier to do when incorporating Markdown into your own projects.
Definitely tables are cumbersome.
Yeah, 100%. That is completely something I am punting on currently. It would be easy to just copy over the solution from (extensions to) Markdown, but it's hard to entirely narrow in on both what tables ought to do and how to make them do it.
If you had a magic wand, what would you have them be more like?
mandelbrot
for y in range(10):
s=''
for x in range(25):
a=[]
for q in range(2):
z=c=x/25*3-2+1j*((y*2+q)/10-1);n=40
while n and abs(z)<2:z=z*z+c;n-=1
a+=[n<5]
s+=" โโโ"[a[0]+2*a[1]]
print(s)
โโ
โโโโโโโโ
โ โโโโโโโโโ
โโโโโโโโโโโโโ
โโโโโโโโโโโโโโโโโโโ
โโโ โโโโโโโโโ
โโโโโโโโ
โ โโโโ
โโ(Opinion) People donโt like generative AI because it made the {insert creativity} too easy. Saw the HN post on โAI music banned from top 40 chart in Australiaโ and people had very strong opinions in both directions.
The hot take: If youโre ok with someoneโs creativity being outsourced to others, then you should be ok with AI doing the same.
If โAI made this and I call it mineโ is bad but โsomeone overseas on fivver made this and I call it mineโ and itโs suddenly ok, time to self reflect.
โฆ
My hot take: from the moment you use technology, be it an instrument, a synthesizer, a DAW, and now AI, it is still your idea, your effort, your time spent, and that makes it yours. Others can do the same if they choose. The same way someone chooses a classic guitar over a synthesizer, one can choose an AI over (insert ancient way of doing things).
โฆ
Youโre rolling the dice whenever you are searching for a sample or a preset in a synthesizer. Eventually itโs what โsounds goodโ, so still the effort is your judgement and the time spent finding that โdice rollโ that sounded well.
I am not a musician, so I lack the jargon to properly explain what I mean.
I used AI for creative writing (nothing too fancy, TTRPG). There, the broader the dice roll, the more generic and uninteresting the results. Slop, if you will. It was surprisingly good to build up on ideas I had however.
I imagine muisic also has building blocks. Melodies, instruments, mixing, etc. AI can perhaps be used in a similar fashion there.
I heard a perspective I sort of like: if AI is a tool then acceptable AI use is, more or less, defined as "when my audience no longer notices or cares". It's dynamic like that. Bad photoshop is detectable and annoying, so are overusing presets. Your artistry needs to expand to meet the tool.
I don't know if I 100% like that or agree. At the same time, it's a pretty straightforward line, a practical take.