whinvik

I always feel like I want to use something like this, but then realize my NeoVim setup + tmux + Ghostty is good enough and I am not ready to learn a whole another system for modest gains.

The friction I have currently is obviously things like port forwarding, in app browser etc.

I keep thinking to try out cmux but haven't gotten around to it.

Funny that its hosted on vercel. Probably because its employee driven rather than top down. Saves all the bureaucracy to get someone to sign a budget item to buy a domain.

Is this article really worth sharing? A speculative headline with no numbers, no estimates, 0 data.

Feels like click bait and HN is submitting to the bait.

Yeah I have always felt GPT 5.4 does too much. It is amazing at following instructions precisely but it convinces itself to do a bit too much.

I am surprised Gemini 3.1 Pro is so high up there. I have never managed to make it work reliably so maybe there's some metric not being covered here.

That gives me slightly more confidence but only slightly.

For example what happens if I use a different async backend like Tokio?

Is this guaranteed by the async specification? Or is this just current behavior which could be changed in a future update. Feels like a brittle dependency if its not part of the spec.

Haven't used it but have seen some online recommendations for gh-dash. https://github.com/dlvhdr/gh-dash

I don't get it. All these are provided by many different agent libs like langgraph, Pydantic AI etc. I thought DSPy was for prompt optimization but I could never wrap my head around that aspect since like Langchain, DSPy seems to hide stuff a bit too much.

So this article seems surprising since it emphasizes more the non prompt optimization aspects. If that was the selling point I would rather use something like Pydantic AI when I already use Pydantic for so much of the rest.

Yeah I have always struggled to figure out why I would use SQLModel.

Big fan of FastAPI but I think SQLModel leads to the wrong mental model that somehow db model and api schema are the same.

Therefore I insist on using SQLAlchemy for db models and pydantic for api schemas as a mental boundary.

This is my current position as well.

I think we are going through the same cycle of http leading to https, the rise of oauth and oidc. Its just way faster now.

Sorry if I wasn't clear but was not talking about demo runs. There are plenty of those. Was more meaning operational speeds having a limit.

Wow I though 300 Kph was some kind of physical limit. I mean every high speed train in the world used to max out at 300.

Now it feels like it was just lack of competition. Maybe now other countries will start producing lines and trains capable of 400 Kph and hopefully its not a China only thing going forward.

Looks very interesting. Can you comment on why you think this model can give comparable performance with less training data?

Another vote for handy. I am using with Parakeet and its pretty good.

Now its mostly about models getting better.

It's weird to see the expectation that the result should be perfect.

All said and done, that its even possible is remarkable. Maybe these all go into training the next Opus or Sonnet and we start getting models that can create efficient compilers from scratch. That would be something!

Came here to ask the same question!

One can put `dotenvx` into the deny list for the agent but there will definitely be ways around of it.

Interesting. That's exactly what I feel about most subreddits. Go to r/Python for example.

It's an endless stream of basic tool/library questions. Put me off reddit quite a bit.

Curious if anyone has experimented with dotenvx - https://dotenvx.com/

When we were trying to build our own agents we put quite a bit of effort on evals which was useful.

But switching over to using coding agents we never did the same. Feels like building an eval set will be an important part of what engg orgs do going forward.

Thanks. I was sure someone was going to make this sooner rather than later and this one seems relatively easy to configure.

I got tired of setting individual allow lists for each CLI, hopefully now I can run them all in Yolo mode while fence does the centralized sandboxing.

I am on a Mac but I develop remotely on a VM, LSP is sometimes so slow, I want to shut it down.

Sorry off topic question but has Docker come up with a easy to use dev solution. I always end up with using Devcontainer: it solves the sandboxed, ready to use dev env.

But the actual experience with developing on VSCode with Dev Containers is not great. It's laggy and slow.

Parakeet is much smaller and for me the perf/speed combo has just been better.

I am often frustrated by PDF issues such as how complicated it is to create one.

But reading the article I realized PDFs have become ubiquitous because of its insistence on backwards compatibility. Maybe for some things it's good to move this slow.

Haha something that I want to try out. I have started using voice input more and more instead of typing and now I am on my second app and second TTS model, namely Handy and Parakeet V3.

Parakeet is pretty good, but there are times it struggles. Would be interesting to see how Qwen compares once Handy has it in.

Sorry for the naive question but specifically for running Claude on a sandbox, why do people decide to use lume as opposed to running it on Docker?

I will be honest. I love that post, makes me want to go see what they are doing.

However, I haven't seen anything from Mozilla in recent years that makes me trust this has a future.

Nice, I actually understood a lot of that post since I am trying to teach myself formal methods. Wrote up a bit here - https://vikramsg.github.io/introduction-to-formal-methods-pa...

I think this is how us engineers always do it but it's almost always the other way around.

Sell first. Building the tech is just an excuse to not learn how to sell. You don't really know what customers really want until you start asking for money.