It makes it super easy to using existing workflows to chain them together into more complex outputs.

All of this withouts nodes.

Early release is out here: https://github.com/svenhimmelvarg/kaleidoscope

For example, I've never heard of Automator. I'm familiar with Zapier, I'll have to evaluate the two situations, then I'll find out that might need to find an alternative that runs on Linux and then I'll have to check if....

These are all simple steps but they all use a non-trivial amount of time for the problem their solving

The other thing is the

Its one of the few subscriptions where it actually feels like money well spent

This leads to the idea that LLMs with existing languages can't really learn new idiomatic patterns.

For new engineers I think new paradigms will emerge that invalidate the need to know the current set of design patterns and idioms. Look at the resurgence of unit tests or the new interests in verification systems.

RTX 3090, Pop OS 24.04 (beta), 4K 43" Monitor,

Nvidia cards worked out the box with no problems

I can focus for hours on end and spend zero mental energy on resizing a window. I had less of that with i3wm but you had to always readjust after a few windows were tiled to your workspace. That final bit of cognitive overload was removed with Niri.

EDIT: Spec: RTX 3090, Pop OS 24.04 (beta), 4K 43" Monitor,

Niri Installed from cargo build, super easy install, make sure you install xwayland-satellite so that you can run VS Code, Obsidian, Zoom, Blender and other strictly X11 applications

One glaring omission is lack of support for proxy docker.io without the project name i.e pulling nginx:latest instead of /myproject/nginx/nginx:latest

The workaround involves URL rewrite magic in your proxy of choice

You need a DSL either supported in the language or through configuration. These are features you get for free in python and secondly JavaScript. You have to write most of this yourself in go

There may be many things that go wrong and how you handle this depends on your data guarantees and consistency requirements.

If you're not queuing what are you doing when a write fails, throwing away the data?

Discord is predominately blocked on a corporate networks. Artifactory ( & Nexus) are very common in corporate environments. Corporate proxies are even more common. This is why I'd hesitate. These are common use cases (albeit corporate) that may not be readily available in the docs.

I find it interesting that he almost equates OpenAI === LLMs and misses the fact that the hype is not purely industry driven. For instance, the number of machine learning papers in the last year has quite literally doubled.

This is also typical of an Americentric view on innovation that we don't report on the quiet revolution happening in education in underdeveloped countries that are a direct result of the accessibility of this unprofitable technology.

I don't think we need killer application right now

We also forget the internet bubble happend first

I think the author is looking at LLMs through the lens of Sam Altman's hype narrative and I wonder why we care so much that

How do you get accurate information on the template structure?

I use Ollama for prototyping and then move what I can to a vLLM set up

How do I serve svelte files using a python or golang backend and still have client side routing? These should have a fairly straightforward answer but I don't think they do.