Huh? No, that's been established since Karpathy coined the term; you don't review the code, only use the agent and don't care about how it was done, just about the results.
The actual interesting stuff is how to use LLMs together with a human, to build high quality code. More "augmenting the human intellect" rather than "autonomous robots building for you".
Overall I'd say if someone handed you a specification that named SSE specifically, you created files with SSE in the name, and the implementation talks about doing SSE, yet it doesn't actually do SSE in the end, it's pretty much on par with code in commercial settings, yeah :) But maybe our bar should be slightly above the ground at least? :)
However, nowadays it is used as a synonym for everything that is somehow generated by an LLM. Regardless of whether it is a spec-driven, carefully reviewed and iterative piece of software or some yolo-style one-prompter with no idea how it was done.
Probably. I've been known to spend weeks planning something that I then forget and leave completely unstarted because other things took my attention!
> Commenter's history is full of 'red flags'
I wonder how much these red flags are starting to change how people write without LLMs, to avoid being accused of being a bot. A number of text checking tools suggested replacing ASCII hyphens with m-dashes in the pre-LLM-boom days¹ and I started listening to them, though I no longer do. That doesn't affect the overall sentence structure, but a lot of people jump on m-/n- dashes anywhere in text as a sign, not just in “it isn't <x> - it is <y>” like patterns.
It is certainly changing what people write about, with many threads like this one being diverted into discussing LLM output and how to spot it!
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[1] This is probably why there are many of them in the training data, so they are seen as significant by tokenisation steps, so they come out of the resulting models often.
> "A typo or two also helps to show it’s not AI (one of the biggest issues right now)."