> Why is PR count or number of issues relevant for the overall outcome?
Agree on PR count but how is number of issues not relevant? If throughout increases 36% but incidents also rise by 40% that’s pretty clearly a net negative IMO.
> The kind of person who copy and pastes from the AI is the kind who did the same from StackOverflow before. The kind of person who insists on understanding things and working through the problem has always been rarer.
Well, this is where I disagree. I have coworkers who used to insist on understanding and now are doing exactly as OP wrote - copy/pasting from the LLM to brute force error messages. I don't know if it's generalizable but this is what I see in <big tech> working on a frontend team with mid to senior level engineers who I respect.
One example a few weeks ago, I was helping a coworker root cause a bug in a React codebase. Pair programming isn't necessarily common but sometimes you see someone banging their head at a problem and you get curious. It turned out there was an effect (a callback that's invoked whenever some state changes) that invokes an API and this effect caused an infinite render loop because the error handling wasn't written correctly. It was something silly like - Call this API if we have no data -> get error -> update state -> call API again because we have no data...
That was almost immediately what I suspected but my colleague was pulling out all the stops usually reserved for when you're desperate or need a sanity check, like logging to stdout after each line. Both my colleague and the LLM were convinced the problem lied in the pagination logic of the helper that invokes the API. He ended up rewriting that helper imperatively and functionally. To his credit, he rewrote it by hand and implemented the recursion correctly but he was baffled when the problem remained. Completely surprised Pikachu face.
I don't think my coworker changed or suddenly stopped caring. It seems much more likely this is a predictable outcome when you lean heavily into AI authoring code for a sustained period of time. I'd also say that in itself is a consequence of the extreme pressure being exerted across the entire company to ship more code and review more code, faster.
> Then they can shrug and say "wasn't me, it was the AI"
Or even worse they hold a fall person accountable. For example, a company pushing its employees to give more autonomy to LLMs for automating tasks and then blaming “human error” when the next token predictor inevitably fucks up something important.
"Fugayzi, fugazi. It's a whazy. It's a woozie. It's fairy dust. It doesn't exist. It's never landed. It is no matter. It's not on the elemental chart. It's not fucking real." - Mark Hanna
Agree on PR count but how is number of issues not relevant? If throughout increases 36% but incidents also rise by 40% that’s pretty clearly a net negative IMO.
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