Also, another difference is the stochastic nature of the LLMs. With table saws, CNC machines, and modern 3D printers, you kind of know what you are getting out. With LLMs, there is a whole chance aspect; sometimes, what it spits out is plainly incorrect, sometimes, it is exactly what you are thinking, but when you hit the jackpot, and get the nugget of info that elegantly solves the problem, you get the rush. Then, you start the whole bikeshedding of your prompt/models/parameters to try and hit the jackpot again.
Absolutely, not understanding why you even ask. Humans are creatures of habits that often dip a bit or more into outright addictions, in one of its many forms.
But it's also a tool that (can) save(s) you time.
This is a guy with 10+ years experience as a dev. It was a watershed moment for me, many people really have stopped thinking for themselves.
The way humans are depicted in Wall-E springs to mind as being quite prescient, it wasn't meant to be a doco
I think part of the problem is that our brains are wired to look for the path of least resistance, and so shoving everything into an LLM prompt becomes an easy escape hatch. I'm trying to combat this myself, but finding it not trivial, to be honest. All these tools are kind of just making me lazier week over week.
I know I know you're going to say (or simonw will) that effective and responsible use of LLM coding agents also requires those things, but in the real world that just isn't what's happening.
I am witnessing first hand people on my team pasting in a jira story, pressing the button and hoping for the best. And since it does sometimes do a somewhat decent job, they are addicted.
I literally heard my team lead say to someone "just use copilot so you don't have to use your brain". He's got all the tools- windsurf, antigravity, codex, copilot- just keeps firing off vibe coded pull requests.
Our manager has AI psychosis, says the teams that keep their jobs will be the ones that move fastest using AI, doesn't matter what mess the code base ends up in because those fast moving teams get to move on to other projects while the loser slow teams inherit and maintain the mess.