It is possible to say the same about the low code solutions, e.g. a perfect UI can be used instead of writing a single line of code. The problem is that creating such a system is too resource intensive and counterproductive, and such a system does not exist. Similarly coding has always some problem that cannot be generalised due to the non existent pattern in training, and creating such a pattern beats the goal of having such a system.
You're talking about net gains in "coding tasks" productivity, I'm talking in productivity gain across the board.
My company deals with an insane amount of customers who use chatgpt to pre-debug their problems before coming to our support. Once they contact our support they regurgitate llm generated BS to our support engineers thinking they're going to speed up the process, the only thing they're doing is generating noise that slows everyone down because chatgpt has absolutely no clue about our product and keeps sending them on wild goose chases. Sometimes they even lie pretending "a colleague" steered them in this or that direction while it's 100% obvious the whole thing was hallucinate and even written by an llm.
I can't tell you how frustrating it is to read a 10 min long customer email just to realise it's just an llm hallucinating probable causes for a bug that takes 2 sentences to describe.
I agree with that idea. For more business development areas, AI slop can slow things down.
I do think that these kinks will eventually work themselves out and actually increase productivity in these areas. People also need to learn that it is not acceptable to just generate some BS and send it to your boss or colleague. That just transfers the real work of understanding the generated content to someone else.
I would disagree. I would argue that if you aren't seeing gains in your productivity, you're either using the tools incorrectly, or you are in some ultra specific niche area of coding that AI isn't helpful on yet.