Totally agree, but then a lot of the same people will be talking about all of the custom instructions/rules/skills/features etc they have set up, so that's eating up a lot of the context window before you even start
When I do use AI, it's just the pure tool itself, and the context is the exact code I'm working with (because I'm trying to see if it can help me solve a specific problem), and I understand the rest of the codebase well enough to know if it's giving me good answers or bad ones
I work with a guy who does decking (gardens, caravans, etc) and builds sheds, fences, things like that and he does very well indeed (he's also incredibly good at it to be fair)
This is an active conversation going on at my day job right now (and I suspect many other peoples too)
Every developer (we have about 100) has Github Copilot, and interestingly some barely use it while others use it a lot (about 70% of usage comes from a handful of devs), and the dashboard shows you exactly who is using which models, and how much
I definitely don't think they will just go along with paying 10/20x more than before without seeing some sort of return on that investment
We've already had the we're spending all this money on AI, why aren't we shipping software faster conversation multiple times
My prediction is that those high users, costing the most money, will be watched carefully (one colleague even suggested half-jokingly that whoever tops the leaderboard should have to give everyone else a presentation on what they spent all those AI credits on)
The sweet spot is to have good competent developers who users AI when it actually makes sense, but aren't dependent on it
I was trying to figure out a nightmare bug that only happened in production and Claude code was able to connect to Google Cloud and read the logs in real time
I recreated the bug in the UI and it was instantly able to see ion the logs what the problem was, then because it had the context of my whole codebase it was able to point me to the exact line of code causing the problem
In my day job, we commonly create prototypes to sell the idea/concept to the higher ups, then if we get the green light, we throw the prototype in the bin and start from scratch to build it out properly.
I find this is where AI is genuinely useful, it lets us prototype an idea a lot faster, make no bones about the fact that it is a buggy proof of concept but lets people see the potential and get an idea for what the final product might look like.