logs suggest it's been 'critically failing' and 'blocked for 68 days' on farmhand introduction, although the logs don't go back far enough (and cut off too early) to really tell what's going on. https://proofofcorn.com/log

my company (mid-size, publicly traded) is mandating [x] hours spent on AI per week. i have no idea how they're planning on measuring this, and as far as i can tell, neither does management.

suppose it's better than counting lines of code, though.

i'm a senior engineer at a mid-size, publicly traded company.

my team has largely avoided AI; our sister team has been quite gungho on it. i recently handed off a project to them that i'd scoped at about one sprint of work. they returned with a project design that involved four microservices, five new database tables, and an entirely new orchestration and observability layer. it took almost a week of back-and-forth to pare things down.

since then, they've spent several sprints delivering PRs that i now have to review. there's lots of things that don't work, don't make sense, or reinvent things we already have from scratch. almost half the code is dedicated to creating 'reusable' and 'modular' classes (read: boilerplate) for a project that was distinctly scoped as a one-off. as a result, this takes hours, and it's cut into my own sprint velocity. i'm doing all the hard work but receiving none of the credit.

management just told me that every engineer is now required to use AI. i'm tired.

because my company is mandating that we use motorboats instead of rowboats.

i can continue to row as a hobby, but i've been very lucky in that my work has always been something i genuinely enjoyed. now that it's become something that's actively burning me out, it's far harder to find time for hobbies and interests.

I'm not in translation, but a number of close friends are in the industry. Two trends I've noticed in the industry, which I think we're seeing mirrored in tech:

1. No one cares about quality. Even in fields you'd expect to require the 'human touch' (e.g. novel translation), publishers are replacing translators with AI. It doesn't matter if you have higher-level knowledge or skills if the company gains more from cutting your contract than it loses in sales.

2. Translation jobs have been replaced with jobs proofreading machine translations, which pays peanuts (since AI is 'doing most of the work') but in fact takes almost as much effort as translating from scratch (since AI is often wrong in very subtle ways). The comparison to PR reviews makes itself.

It is not entirely true that no one cares about quality. I'd like to stay optimistic and believe that those who are demanding on the quality of their production will acquire sufficient market differentiation to prevail.

After all, this has been Apple strategy since the 80's, and, even though there were some up's and down's, overall it's a success.

> It is not entirely true that no one cares about quality. I'd like to stay optimistic and believe that those who are demanding on the quality of their production will acquire sufficient market differentiation to prevail.

Maybe, but it probably requires a very strong and opinionated leader to pull off. The conventional wisdom in American business leadership seems to be to pursue the lowest level of quality you can get away with, and focus on cutting costs. And you'll have to fight that every second.

I don't think that's true at the individual-contributor level (pursing quality is very motivating), but they people who move up are the ones who sound "smart" by aping conventional wisdom.

> After all, this has been Apple strategy since the 80's, and, even though there were some up's and down's, overall it's a success.

I might give you that "since the late 90s," but there have been significant periods where that wasn't true (e.g. the early mid-90s Mac OS was buggy and had poor foundations).

someone still will, but quality will become really expensive

In other words, AI was used to massively depress wages and lower quality of life of employees while outputting worse results. Which is what is now happening in software.

it feels good because we've turned coding into a gacha machine. you chase the high from when it works, and if it doesn't, you just throw more tokens at the problem.

i've seen this fairly often with internal libraries as well - a recent AI-assisted PR i reviewed included a complete reimplementation of our metrics collector interface.

suspect this happened because the reimplementation contained a number of standard/expected methods that we didn't have in our existing interface (because we didn't need them), so it was considered 'different' enough. but none of the code actually used those methods (because we didn't need them), so all this PR did was add a few hundred lines of cognitive overhead.

I’ve seen this as well as PR feedback to authors of AI assisted PRs: “hey we already have a db driver and interface we’re using for this operation, why did you write this?”

language-based professions like translation have been dying for years and no one has cared; they're not about to start now that the final nail's been put in the coffin.

generally speaking for han chinese folks, surnames are one character and given names are one or two characters (with two being more common, usually). so if you see a name that's 1-2 or 2-1 (i.e. liu yifei) and it's not one of the few known multi-character surnames, then you can safely assume that's their given name.

for a 1-1 name like yao ming, it's a little more difficult. some characters are definitely more common as surnames than others - the chinese term for 'common people' (百姓) actually refers to an old classic text where they compiled all the surnames they knew of! so when i see the name yao ming, i immediately recognize that 'yao' is a fairly common surname and 'ming' is not, and thus it's more likely (but not guaranteed!) that 'yao' is the surname here.

there's also some cases that are ambiguous when romanized, but not ambiguous in chinese. for example, consider the name 'wang chen,' where both 'wang' and 'chen' are common chinese surnames. however, if i saw it written out as 王, i would be able to recognize that 王 'wang' is a character that's primarily used for surnames, while 晨 'chen' is not.

chinese names can absolutely be gendered - for example, if i met a 璐, there's a 99% chance that name belongs to a woman because of its meaning (beautiful jade) and its character composition (王 radicals tend to be feminine). i feel like gender-ambiguous names have become more common in recent years, but maybe that's just me not keeping up with naming trends.