btop more like b(eautiful)top

Apple is so good at naming, y'all

https://www.apple.com/newsroom/2026/03/apple-debuts-m5-pro-and-m5-max-to-supercharge-the-most-demanding-pro-workflows/

Explanation: super cores, performance cores, and efficiency cores are all different types of CPU core that Apple can make.

Apparently, the M5 originally launched with super cores and efficiency courses, but Apple accidentally called the super cores "performance cores"... I think

Gosh this is so shitty... We really wanna review it lol

https://youtu.be/GSrIeDHbZhI

One thing We notice every time We work on code with an LLM, is that it has a lack of forethought which is really dangerous.

Like right now, We're designing a feature for SHELF which allows devs to reference objects without nesting them. Standard database shit.

Claude 4.6 Sonnet suggested a property wrapper that presents as the desired type, but has functions on the wrapper which can sync it. The end result is that devs would then need to access its sythesized wrapper instance to manually sync the data, defeating the whole point of using a property wrapper instead of just a wrapper type.

The solution it gave would technically work, but it'd be shitty and pointless.

We see this over and over again when asking LLMs to generate code. A mutex which deadlocks if you use it wrong, an editor screen where only some of the fields sync the changes, embedding the private keys in the config files, etc.

All shit that technically accomplishes the stated goal, but in a way that is effectively pointless.

We wonder if this is related to LLMs failing to perform spacial reasoning. Perhaps foresight like this is similar, something that'll require a new architecture to conquer.

Still prefer LLM autocomplete over heuristic, though. Just gotta understand what it's suggesting.

Another Proton L

Context ☝🏽️

Android moment

OMG this font, Datatype, is amazing

this screenshot ☝🏽
is how it renders this text 👇🏾:

{l:Server Errors {b:20,25,52,36,67} Body Weight {l:42,21,53,67,69,43,61} 38% signed {p:38} Trainings Done {b:71,19} CO2 Deliveries {l:33,46,13,13,89,12,76,39,44} 14% funded {p:14} Daily Mood {l:25,25,64,22,72,14,33,21,79,67} 70% milestone {p:70} Attendees {b:64,91,87,17,22,76,17}

Speaking of hexed font files, here's one which is also an LLM

https://fuglede.github.io/llama.ttf/