You can always use your own code however you want. However, if your project starts to get contributions from other people, that’s where it can start to become more muddy.

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/

Or Majora’s Mask but with wave dashing

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.

Reminds me, Malcom Gladwell’s “Outliers” book had a section about his interesting observation that pro hockey players’ birthdays are skewed to the earlier months of the year. He attributed that to a kind of butterfly effect:

1. Youth hockey leagues set league cutoffs by age, and mostly all start at the same time.
2. The early month kids are slightly older, bigger, and stronger
3. Since they are better at the very beginning, they get more playing time, more encouragement, maybe visit more “all-star” events, where they might get extra coaching, etc.
4. eventually those kids actually just become better, because they had a better environment to grow.

I mean idk how accurate this exact instance is, but I feel it’s a good thought experiment in thinking of how seemingly insignificant parts of the environment (like when in the year all the youth hockey leagues start) can impact whatever talent is. The whole nature vs nurture thing.

Anyone got store recs for non-english books? Or that mostly just gonna vary a ton by language?

Yupyup I understand that feeling for sure. I have the same nitpick problem. Just figured I’d mention this one because it’s the least dongly feeling dongle that I’ve tried by a large margin, and so has become the only one I’ve actually continued using.

fwiw, I found the form factor of this dac to be much more enjoyable than the pigtail adapters, because it feels more like “part of the headphone cable”: https://www.ddhifi.com/en/product-review/11321/

I’ve found that for me, the most “prone to damage” part for usb-c audio is just the usb-c connection… so idk how much a usb-c headset improves over an adapter… I just want them to add back headphone jacks. 😭

Just wait until you taste “Songs You Recorded in High School” 😬

heh… p sure this is the lighthouse that made me decide to buy a camera. Me trying my best with an iPhone SE 6 years ago:

Fwiw, on my m3 + max ram, I also was recording 1080p 30-ish minute obs videos for a while running large Ableton Live project playback + a facecam, and (while I don’t remember specs specifics) I didn’t find it to be unstable. I don’t do heavy video editing, so I’m not sure about the requirements, but for obs in 1080, it felt fine for me. I think I also exported some edited 4k footage at one point though, and I seem to remember rendering that one took a solid amount of time, so if you think you might move to 4k, pro might be more appropriate.

But I remember having specs reservations when getting my air, and I have not regretted it at all. Especially when I see my friends lug around their monster of a laptop. Those pro machines are thicc