I used to see this with students in calculus who abused the tutoring resources. They'd have tutors just work problems (often their homework...) in front of them. "Ah! Obviously that trig substitution integral worked that way. Oh, of course, that proof is very obvious in retrospect." And then they'd walk away from the exam with a 30% and no idea how their 20 hours of "study" for it didn't result in the same performance as their peers who worked problems, read the materials and asked questions, etc., got.

Most AI use is that same in my experience. "Show me how the fundamental theory of calculus works." The LLM puts together a very elaborate and flashy presentation that they skim. Great. That's no different than reading a text book. Even if you ask the LLM questions and have it elaborate on things, you've never once done one of the most important things a student can do: spend time confused trying to work hard at understanding something that's not obvious. The LLM will make it obvious at every point. Total lack of friction. Works about as well as a spotter who does the lifting for you.

Raising the difficulty only matters for the (imo) less important part: the dick measuring competition between the very top teams.

The actual point of CTFs was usually to keep your skills sharp and stay learning. Eventually you build your own challenges, thereby completing the "have it taught to me, then do it myself, then teach another person" three step process towards mastering concepts.

You can just say "let the people who want to learn from it do so" but honestly the entire culture of learning in the US at least is DEAD. We turned "education" into a rote system of maximizing incentives to the extent that that's all the youth know it as, and (increasingly) all educators can do. It's just gone without some kind of major reckoning, and we all know things will just collapse before that happens. The ball is in the court of whatever country can learn how to force its youth to learn the real way and use AI productively only AFTER learning the concepts it's being used to accelerate.

Also "reactionary" haha

I plan on getting one for this use case. I do most dev work on servers via either something like VSCode remote or just through Vim. Tailscale and make it easy to use my Mac Mini from anywhere. I can get the Neo on an educational discount, making it $500 and a pretty easy choice.

A while back I went into an Apple Store and opened up as many huge applications (Logic Pro, etc.) and like 50 browser tabs and the Neo still worked fine. I think it will be a good thin client.

It's not a matter of preference

Yeah man I don't know if mommy and daddy are paying your rent and healthcare (as I often see from people with this attitude). Or maybe you're one of the 45 year old tech workers whose mid life crisis involves a music project no one will listen to and going to work on some startups with your FIRE nest egg until you come crawling back to a big tech company. But for now I, like most millennial Americans, am reliant on wage labor to afford a dignified life in a tolerable town.

Part of it's that the whole point of going into this industry is that I love coding and have been doing it since I was 8. Part of it is that I'm a control freak and it makes me uncomfortable to have to trust AI generated code. Sure, I already trust interpreters and compilers, but those are much more deterministic, and they don't generally do anything I have to be wary of. Part of it is that anytime I've used Claude to write stuff (using Opus 4.7 via an API key), I've had to handhold it when doing simple things (telling it repeatedly that a given column doesn't exist in Snowflake's task history table and eventually just giving up and taking it out by hand) and had to remove tons of completely pointless Python code it generates. The big difference is that the people in the first camp don't seem to care enough to check. Someone at my company used Claude to write 20k lines of code this past Friday. No way he read and scrutinized all of that in one day.

The other big thing I've noticed is that a lot of the people using it extensively seem to just be spitting out API endpoint after endpoint. Just doing endless CRUD with some light business logic. Yeah, it's not too hard to automate that with AI without any major issues. Hell, back when Ruby on Rails was hot, it was so fast to write those kinds of things with it that I could spin up things as fast as AI is doing now. Full websites or APIs in an hour or two because its syntactic sugar and scaffolding did what AI does with the FastAPI codebases I see these days. You could go from an ER diagram to a working app in minutes sometimes. I don't care that much if that kind of work is automated.