whazor

i am replying to the 'feeling of having missed out' part

it is not too late to build a better computer and to also be in a working environment that has fun

we are nowhere near the perfect computer yet

Like some kind of spy movie where they catch a spy and give the spy the option to work for them.

I've noticed that people (including myself) are becoming too lazy with LLMs.

Trying to become even lazier by skipping code reviews and then vibe-coding formal software verification will get you into trouble.

In my experience with software verification, perfect is the enemy of good. My recommendation is to start with a software design you actually understand, and then try to understand how to map your requirements to something you can prove.

Switch to Jellyfin plus a VPN like Tailscale.

The trick is finding the best client for the device you want to watch on. There are quite some options.

This is the second time people are getting hacked via Plex vulnerabilities since I have been counting.

welcome to the new way of software distribution, blogs and tweets are the prompts you use

I do agree that Opus 5.5 (and Fable) beats me at coding, but I haven't found this to be the case yet in software design.

Update: Yes!!! VLANs are up and running.

Today when you compare:

1. Fable as software designer and me as reviewer

2. Me as software designer

3. Me as software designer and Fable as reviewer

Then in my opinion, best design comes from 3, then 2, then 1.

I got two GL.Inet devices:

- Flint 2: very happy with this. I can do any kind of OpenWRT setting I want

- Flint 3: super unhappy!! changing VLAN settings breaks the entire router.

Why? Flint 3 uses a chip with encrypted vendor blob (Qualcomm) and Gl.inet just hacked the drivers in a way is not compatible with OpenWRT.

But maybe I should let an agent reverse engineer the driver and add correct support myself?

Edit: i haven't checked the status in a while, but seems like last months support for this device changed a lot.

When people open up their brand-new Mac for the first time and look at available storage, they can be disappointed.

The benefit of Pi in my eyes is that the TypeScript interfaces make it easy to build your own sandbox.

This will make it easy to add Pi.dev to a web application and connect it via WebMCP or a backend MCP.

Meanwhile Fable 5 and Opus 5.5 are in a different league.

Nixpkgs is quite explicit about how to produce the distribution. You can rebuild the entire distro from source and backup the source code for every package.

As a normal NixOS user, I know how to do this. It would be quite some effort, but not especially difficult. Additionally, for a government they have the servers to set up a build farm.

They previously used openSUSE and then Fedora. But both have companies behind them, where-as NixOS does not. And with NixOS they are more sovereign.

There are two problems that arise from cheap code:

1. You get complexity back at the speed that you add code. Also the complexity compounds.

2. As a human you are still responsible for your code, and you need to understand how the important parts of the code base work.

When you combine these problems, you get a complicated code base where you don't understand the important parts.

That is why software design is getting a comeback. It actually helps with both problems. Less complexity and more understanding.

Software engineering is so back.

When designing systems, you want the important details to be right. Especially with authentication and authorization.

From an architecture level, you can know which classes are important to review and which ones are not.

It is insane from a consumer point of view. Luna is cheap and smart enough to do many agentic tasks. Cheap enough so that you can put it on a website without auth.

The Jev model is economically, but also in terms of compute, a much more efficient model. A normal LLM goes token by token, each token in a separate step. Whereas Jev just returns all the results the first round. So it is much better at classification than LLMs.

Compared to traditional ML classification, Jev works without training, like a LLM.

MCPs are winning because within the ChatGPT and Claude apps, there are Plugin stores. These plugins are one-click installation MCP servers, with support for authentication. This is what business users are using.

The most interesting use case in my mind is skipping law suits. Obviously you need lawyers in court. But lawyers are people you are basically paying to fight for you.

Instead, if you resolve your dispute outside of court, you don’t need a lawyer. If both parties use ChatGPT to find the relevant laws or read contracts, they could come to an agreement without expensive legal fees.

Given the approach from the article, you can commit the hints to git and run tests for verification. The model would be used during coding.

A question I have, with the type { output: string }, would the model not become a LLM? And if it does, shouldn’t it cost the same as a LLM for output?

There are also people arguing that children should have no internet access because its harmful.

But children do have access to internet and often with some protections.

This is also how I feel about AI, where a full ban is the lazy way out. Similarly like the internet, it is not possible to 100% protect a child every potential harmful AI interaction.

This voice model can do tool calling. So as long you give it powerful tools, I believe it to be useful.

I can understand the concerns but at the same time it feels weird to deny young people the ability to make their ideas reality. I got proper internet access when I was 12 and that is how I taught myself how to program.

Once you know this, you cannot unsee this in every AI design everywhere

I'm confident that Muse can do lots of agentic tasks succesfully for normies on outdated models. Like buying sneakers, booking appointments, dealing with government forms.

Yeah and you probably have to. An ETF easily has >1000 different stocks and even being weighted. So it has a completely different risk appetite by being so averaged.

But ETFs do have to follow particular rules defined by their product description. So it is still interesting to benchmark against.