tbf, I don’t know how feasible it is to remove asbestos without employing 4 year olds.

I would say deep thinking work, I average around 3-4 hours, but range between 0-8 hours. Like if I really feel in zone, it’s easy to go hard, but if I didn’t sleep well, or had too much caffeine, or didn’t eat enough, it’s just joever. I think months of grinding is possible with the right motivation, but I find that trying to force that motivation is pretty hard; I think that’s often more environment-based, rather than solely individual effort (ala being in a class of very motivated individuals)

The important part for me is trying to start every day (or whatever your schedule is), because it can be hard to know how well I’ll concentrate until I try for 30 minutes or so. And consistency over a long period of time is key.

edit: oh, fwiw, specifically for Chinese, I have been building this recently… although it’s not done yet. https://hanzi.bpev.me/

ohhh right. I do that, too. But not to the fainting level of effort.

TBF I’ve been choking on water since I was a wee lad. I just drink too aggressively. A drinking problem, of sorts.

I have been using Graphene until last month (temporarily off it because my phone picked a fight with a rock and lost). So just going off memory. But compatibility is in a much better place these days. I don’t recall having had any compatibility issues besides banking apps and “pay with phone nfc” over the last few years.

Mmm it sounds like you’re using it in a very different way to me; by the time I’m using an LLM, I generally have way more than a general feel for what I’m looking for. People rag on ai for being a “fancy autocomplete”, but that’s literally what I like to use it for. I’ll feed it a detailed spec for what I need, give it a skeleton function with type definitions, and tell the ai to fill it in. It generally fills in basic functions pretty well with that level of definition (ymmv depending on the scope of the function).

This lets me focus more on the code design/structure and validation, while the ai handles a decent amount of grunt work. And if it does a bad job, I would have written the spec and skeleton anyways, so it’s more like bonus if it works. It’s also very good at imitation, so it can help to avoid double-work with similar functionalities.

Kind of shortened/naive example of how I use:

/* Example of another db update function within the app */
/* UnifiedEventUpdate and UnifiedEvent type definitions */

Help me fill in this function

/// Updates event properties, and children:
///   - If `event.updated` is newer than existing, update as normal
///   - If `event.updated` is older than existing, error
///   - If no `event.updated` is provided, assume updated to be now()
/// For updating Content(s):
///   - If `content.id` exists, update the existing content
///   - If `content.id` does not exist, create a new content
///   - If an existing content isn't present, delete the content
pub fn update_event(
    conn: &mut Conn,
    event: UnifiedEventUpdate,
) -> Result<UnifiedEvent, Error> {

100%. As a solo dev who used to work corporate, I compare it to having a jr engineer who completes every task instantly. If you give it something well-documented and not too complex, it’ll be perfect. If you give it something more complex or newer tech, it could work, but may have some mistakes or unadvised shortcuts.

I’ve also found it pretty good for when a dependency I’m evaluating has shit documentation. Not always correct, but sometimes it’ll spit out some apis I didn’t notice.

Edit: Oh also I should mention, I’ve found TDD is pretty good with ai. Since I’m building the tests anyways, it can often give the ai a good description of what you’re looking for, and save some time.

I’d probably agree with them 😂 . This is a cool video thanks for linking!

I mean, that very well could be so! After all, I’ve only lived during my timeline, so recency bias probably does make changes seem more dramatic 😂 . But I do feel like computer usage has created a pretty significant change in how music is composed and produced compared to prior technology, and a lot of those innovations are relatively recent.

? I mean I’m not disagreeing with you. Each of these step changes increased the usage of technology dramatically. I’m not really naming dubstep as the instigator as much as much as I’m just using that to describe the general point in time where I felt like computers became more prevalent as the defacto composition tool. I feel like this is around the time where computer music has really evolved in usage in all genres. For example, the amount of computers in new orchestral scores right now is wild. Of course it was used long before this, but there’s a big difference between usage in specific genres and/or to make music stand out, and it being a part of the general palette for every genre.

I would say no.

Honestly, since directly after the dubstep craze era, there has been suuuuuuch good music, because I feel like that’s when electronics became much more mainstream for ALL musicians to play with. Prior and during that time, I think a lot of electronic music was about experimenting with sounds. But during that era I think was when everyday musicians got comfortable with the soundscapes, and started incorporating all their other music knowledge and to make more varied, complex, and interesting stuff.

The problem is just finding the good music, since it can be so quick for anyone to produce and distribute it. There’s just way too much.

Fwiw, this was also on HN yesterday. Never tried it myself, though:

https://news.ycombinator.com/item?id=39941232

Whoa those space ones are really cool!

It’s like you’re building headphone chimeras. I didn’t realize you could just buy brand parts like that!

So I’ve been trying to learn Spanish and Chinese recently, and as a programmer, I’ve also been making a few tools to help me with it! Right now, the first works, and the second is…. well it kinda works, but it’s more in-progress

1. Emoji Flashcards - http://flashcards.bpev.me

Generates Emoji-Audio-Text flashcards with audio in a bunch of languages (meant to be used with Anki). The idea is that it’s better to avoid using your native tongue when learning a language, so use common visual images (Also, please help fix my translations 😂)! But my friend just vetted the Japanese deck, and I’ve been updating the Mexican Spanish deck as I go, so maybe those ones are pretty okay right now.

2. Multireader - https://github.com/bpevs/multireader

For reading e-books with select-to-translate, so I can read a book in another language, and highlight when I don’t know a word. I want to make it create flashcards from the words I highlight.