I personally really enjoyed Watch Dogs: Legion. It wasn't so much that each individual was very unique. Moreso the concept of being able to become anyone.
In practice I think a lot of engineers would do this. My recommendation would be to avoid this at all costs. In my opinion, the way to scale a codebase with AI is to have some part of the codebase that is reserved only for human hands. You need to be able to look at something written, and to know that it expresses human intent. Once you deviate from that constraint, then you might be even worse off than before, because now you have 2 sets of generated source code to sift through, not 1.
While excessive screen time can certainly be a problem and the specific content matters there is nothing inherently wrong with a small amount of age-appropriate YouTube content consumption.
Also, in my experience, LLMs seem to love to say something went "dark" or "silent", to mention a "generation" of people, and to say something "matters". "no corporate filter" also seems like a strange thing to say.
Em-dashes were in common use long before LLMs existed — anyone saying that’s a sign of LLM use should not be listened to. They’re used by LLMs because they were trained on good writing and we shouldn’t avoid using them any more than we should stop using correct punctuation for the same reason.
> anyone saying that’s a sign of LLM use should not be listened to
You don't need to believe me. You can read the studies about its statistically higher occurrence in LLM writing vs human writing (https://arxiv.org/pdf/2603.27006) or you can do the analysis yourself.
Also, no one said you should stop using them. But overusing them, along with emulating some of the other common traits of LLM generated writing, will give people the impression that you didn't bother to write something yourself.
You’re misunderstanding the problem: LLMs using emdashes more than the average human still doesn’t tell you that the poster you’re interacting with now is an LLM and not one of the many humans who used emdashes before LLMs existed and are the reason why LLM training picked that up as a good trait. Humans shouldn’t stop writing well just because bots were trained to mimic them.
One other problem with this as a heuristic is technical: they used to be hard to enter on Windows so mostly only professionally-edited text there had em-dashes while the ease of entry on Mac, iOS, Android, and to a lesser extent Linux meant that they were more common there. I suspect that this list disproportionately lists Mac users:
Honestly, I simply owned the domain name and think it's mildly amusing. I wouldn't necessarily say I think it's better by any means. Not yet, at least.
There are several things I dislike about some of the existing services though:
1. Most are extremely invasive in regards to personal data and reading their terms makes it clear what their goal is (selling your data either directly or via buyout).
2. Everything constantly tries to push you through their loop: internal messaging, apps, whatever. I'm tired of it. This allows a recruiter to email a person directly.
It's all hosted on free tiers at the moment, so It's really no consequence to me one way or another.
Some changes certainly can be. If the model produces the exact same output for a fixed seed across a variety of inputs after a code change, I think it's reasonable to expect that the change is correct. There are also mathematical transformations that can be applied in some cases that are provably correct. (Not suggesting there's necessarily anything of this nature that will lead to 1,000x improvement though.)
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