300k lines of AIslop that probably would've been 20k lines of code from a human. And the human has no ability to maintain it, or to reason about it.
1. assumes most humans write good code (or even better than LLMs)
2. will stick around to maintain it
after 30 years in the industry and last 10 as consultant I can tell you fairly definitively that #1 cannot be further from the truth and #2 is frequent cause of consultants getting gigs, no one understand what “Joe” did with this :)
You can go look at his GitHub but it's a bewildering array of projects. I've had a bit of a poke around at a few of the seemingly more recent ones. Bit odd though as in one he's gone heavy on TS classes and another heavy on functions. Might be he was just contributing to one as it was under a different account.
And a lot of them seem to be tools that wrap a lot of cli tools. There is a ton of scaffolding code, to handle a ton of cli options. A LOT of logger stmts, one file I randomly opened was a logger stmt every other line.
So it's hard to judge, I found it hard to wade through the code as it's basically just a bunch of option handling for tool calls. It didn't really do much. But necessary, probably?
Just very different code than I need to write.
And there are some weird tells that make it hard to believe.
For example, he talks about refactoring for useEffect in React but I KNOW GPT5 is really rubbish at it.
Some code it's given me recently was littered with useEffect and useMemo when it wasn't needed. Then when challenged it got rid of some, then changed other stuff to useEffect when again, it wasnt needed.
And then got all confused and basically blew it's top.
Yet this person says he can just chuck a basic prompt at his codex cli, running GPT5 and it magically refractors the bad useEffects?
How are we getting such different results?
My comment was more geared towards an insane amount of comments on myriad of "AI" / "agent coding" posts where soooooo many people will write "oh, such AI slop" assuming that average SWE would write it better. I don't know many things but working with these tools heavily over the last year or so (and really heavily last 6 months) I'll take their output over general average SWE every day of the week and twice on Sunday (provided that I am driving the code generation myself, not general AI generated code...)
And yes refactoring sometimes re-introduces these, so it's not a perfect solution.
Having looked at the code a bit more, all I can say is that it's a lot of code to do little.
There's also a lot of naive error throwing going on.
And he seems to debug using logger stmts.
They're not scalable projects, you couldn't write enterprise software the way those projects are written. You would end up with such a volume of code.
2. Even when humans write crappy code, they typically can maintain it.
by now I have shipped over a million lines of code written by LLMs (many others have as well) so 0% maybe in the hands of my 12-year old
> …they can typically maintain it
who exactly is “they”?
you either learn and know how to use tools as SWE professional that you or you don’t…
Now what the guys above the programmers' paygrade knew was that the aim of software development wasn't really code, it was value delivered to customer. If 300k lines if AI slop deliver that value quickly, they can be worth much more than the 20k lines of beautiful human-written code.
Alternatively, maybe folk who're exposed to more codebases are the best off.
Or combine the two for wizard.