Right now the AI LLM PRs we're seeing are just introducing more work for other people, while these so-called builders are looking good with their new dashboards and functionality they're demoing.
But you can't talk to them about the flow of the code. You can't ask them for their thinking as to why certain things are.
It's not built up from the ground with experience from x people taken into account. It's materialized from nothing, with no foundational separation, and barely any abstractions.
No one wants to touch it. The PRs are too large, and the 'authors' of the PRs aren't on call with us.
They get all the glory, but do none of the work.
It's kinda like designing a house and then sending it to an architect and engineer saying: make this work.
You can absolutely do this. It's even right most of the time.
You even have a fair chance of getting a response like that when there isn't anything wrong and the question wasn't rhetorical - which perfectly illustrates the level of the genuine understanding LLMs operate at.
A lot of average people are producing gigantic messes. At least previous to this they were gated by their mediocrity.
I have never seen anywhere in the world people that hates so much the working class as people do in the USA.
In my country the average employee is competent, they do their work and create wealth for the nation.
Again, only in the USA people think that billionaires are the ones creating value. Total non-sense indoctrination.
Not sure if that's true or if it might be influencing what you're seeing, but it's a thought.
**Lead with the answer when asked how/which/whether.** Name the command/mechanism first; a question seeking understanding isn't a go-ahead to execute. Answer, then offer to act.* EDIT * What's with the downvoting? That's a correct description of what happened. You can't ask an LLM why it did something and expect a coherent response, because there's no thinking chain, and no stored thinking state... At best, you can get a reconstruction of how the context relates to the output (basically a summarization of the context).
There are plenty of valid criticisms or warnings about over-reliance on AI coding, but this is not one of them. Today, I am using a semi-autonomous agentic coding system which has an `interview` functionality built in - when it spits out the PR from the input, if you have questions about the motivation or context for a particular choice, you can start up a clone of the original agent in a sandbox to question it.
Now, you might claim that those responses aren't always reliable, accurate, or consistent, and that claim has a little more weight (though, in my experience, decreasingly so) - but it is _certainly_ not the case that you cannot interview an agent about choices made. I'm literally doing it every day.
I've never worked at a company that didn't have a technical backlog measured in years.
Literally nothing works, all the timers/time counters are different across the pages, constantly commands hardware to do stupid shit, breaks during critical moments/in front of clients.
Eventually mgmt had to institute change freezes for high profile events because the team was breaking too much shit all the time.
The average C suite dipshit doesn't realize that the performance drops off a cliff once your project is more than some fraction of the context window so they will make pretty dashboards all day long but once you need to cover all the edge cases of a real system it all explodes.
AI isn't trained on the type of software style we'll need to create systems using AI, it's trained on how we used to write software. It doesn't reuse code or elegantly structure annoying, it just adds more code until the thing builds and passes some fake tests, even if half of it is functionally dead/unused.