Which do you think is ?
Any conversation
โฆ
Microservices.
Not really programming, as this is more on the architectural level.
Microservices is a valid approach when you need to address massive scale. The thing is, I have seen it applied to things that could realistically serve its audience in a handful of modest servers with a less fashionable approach.
It was done under the guise of simplification; each individual microservice was in fact very small. But this at the cost of absolute spaghetti architecture.
Overvalued, maybe. Extremely valuable, yes, though.
For sure. We're well past the point of being able to reasonably claim that the tools have no practical use.
But I share the article's skepticism that LLM-based AI will "produce a fully automated drop-in replacement for most knowledge workers". Which it at this point has to in order to justify these companies' stupendous valuations.
Tomorrow no but there will always be the โhopeโ which is enough for the next 20 years before giving up. Which meanwhile would be replacing larger and larger chunks of the workforce so it wonโt really matter, weโll be adjusting our lives around it as well so we meet in the middle.
Tesla has been overvalued for over a decade with the promise of โfully autonomous carsโ and itโs still not losing its value, despite not meeting that (and probably never will, as the computation necessary to achieve it is bounded by physics).
Hello to friends. Holla for tools.
๐จโ๐ป : , , and Pragmata Pro
๐ช : NotePlan
๐ง : Overcast
๐ง : Allume
๐๏ธ : Mark Two (EDC), Pen Type-B
๐ณ : Anisota
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).
This #tome about #Tcl/Tk has me re-evaluating my plans to move to the woods to be a carpenter hermit.
Now I want to move to the woods and be a programmer hermit.