That's kind of the point here. Once a dev reached a certain level, they often weren't doing much "relaxing code typing" anyways before the AI movement. I don't find it to be much different than being a tech lead, architect, or similar role.
As a former tech lead and now staff engineer, I definitely agree with this. I read a blog post a couple of months ago that theorized that the people that would adopt these technologies the best were people in the exact roles that you describe. I think because we were already used to having to rely on other people to execute on our plans and ideas because they were simply too big to accomplish by ourselves. Now that we have agents to do these things, it's not really all that different - although it is a different management style working around their limitations.
Exactly. I've been a tech lead, have led large, cross-org projects, been an engineering manager, and similar roles. For years, when mentoring upcoming developers what I always to be the most challenging transition was the inflection point between "I deliver most of my value by coding" to "I deliver most of my value by empowering other people to deliver". I think that's what we're seeing here. People who have made this transition are already used to working this way. Both versions have their own quirks and challenges, but at a high level it abstracts.
LLMs are just a programming language/compiler/REPL, though, so there is nothing out of the ordinary for developers. Except what is different is the painfully slow compile time to code ratio. You write code for a few minutes... and then wait. Then spend a few more minutes writing code... and then wait. That is where the exhaustion comes from.
At least in the olden days[1] you could write code for days before compiling, which reduced the pain. Long compilation times has always been awful, but it is less frustrating when you could defer it until the next blue moon. LLMs don't (yet) seem to be able to handle that. If you feed them more than small amounts of code at a time they quickly go off the rails.
With that said, while you could write large amounts of code and defer it until the next blue moon, it is a skill to be able to do that. Even in C++, juniors seem to like to write a few lines of code and then turn to compiling the results to make sure they are on the right track. I expect that is the group of people who is most feeling at home with LLMs. Spending a few minutes writing code and then waiting on compilation isn't abnormal for them.
But presumably the tooling will improve with time.
Well designed ones do, at least. LLMs, in their infancy, still bring a lot of undefined behaviour, which is you end up stuck in the code for a few minutes -> compile -> wait -> repeat cycle. But that is not a desirable property and won't remain acceptable as the technology matures.
It is quite possible the tools will never improve beyond where they sit today, sure, but then usage will naturally drift away from that fatiguing use (not all use, obviously). The constant compile/wait cycle is exhausting exactly because it is not productive.
Businesses are currently willing to accept that lack of productivity as an investment into figuring out how to tame the tools. There is a lot of hope that all the problems can be solved if we keep trying to solve them. And, in fairness, we have gotten a lot closer than we were just a year or so ago towards that end, so the optimism currently remains strong. However, that cannot go on forever. At some point the investment has to prove itself, else the plug will be pulled.
And yes, it may ultimately be a dead end. Absolutely. It wouldn't be the first failure in software development.
