I for one, have far more rigorous quality checks in my hobby projects (where AI coded), than I ever could justify when I hand-coded them.

I'm not claiming to be everybody, but surely a good portion of the population are using these technologies similarly.

[1] Yes, we can argue that LLMs are dumb, also. But they magically do "get" your intent with your prompt, unlike the search engines of yesteryear.

I've literally been saying "I can't believe the date is X and we still have to put up with this" for around 25 years now.

I'm pretty sure Waymo does this. It's hard to imagine not using this information, it's basically 50% of what I do when driving (e.g. that kid that was running on the sidewalk suddenly disappeared from view in an unexpected way; I wonder if he's about to cut across the street, etc).

I've bounced off NMS several times, despite having tried quite hard to get into it. So, my take is based on ~20 hours of early game, from 2025ish. Probably the best parallel I can draw is to Elite: Dangerous, which I played for several hundred ours before getting bored of it. What I find lacking in both games is that there's no _meaningful_ emergent gameplay that spawns off the procgen. Everything is wildy different on each planet, yet very same-y, because none of the differences really play into each other. In both, one can discover random biomes and creatures, but it's not like they are inherently interesting, they are mostly just following the same scripts.

Contrast this with something like Dwarf Fortress, which takes a slightly more in-depth approach to procgen, one where things have history, and in many ways, things "make sense". Or Rimworld, where the game tries its hardest to conjure up a narrative for you, dynamically, but still in a sandbox. So, basically, NMS is a perfectly functional sandbox game, and I have huge respect for them for keeping on working at it for so many years. However, it doesn't scratch my "hardcore simulation / mastery" itch, and so far I haven't been grabbed by any of its story generation. It just felt like a long series of fetch quests and "collect them all" games.

I think when people are irritated by the "hallucination" aspect of LLMs, they are often running into something of a slightly different nature. I mean, firstly, there seems to be a higher-than-normal ratio of these "little mistakes". And secondly, there are some pretty odd ones - e.g. in my team, Claude regularly just straight up makes up Jira ticket numbers, and then refers to them with high confidence. I guess what I'm saying is that a human would probably not just make up an id, and run with it (they may be off by one, or mix two up, etc). In my opinion, these can be successfully treated, but I guess you can never fully eliminate the tendency that irks people.

I would normally advise against such efforts for a variety of reasons (such as inaccurate tracking, etc), but specifically under pi, this mechanism has been extremely well behaved and accurate for me.

I think the hate typically comes from the mis-application of various tools; overly complex solutions for simple problems. There's nothing wrong with patterns per say, or frameworks that have complex building blocks for every conceivable permutation of relatively common issues. However, when people reach for unnecessarily complex tools out of laziness/habit, some hate is justified. I suspect this is very similar to what you're saying, and of course, it's not OOP specific. Functional languages have their patterns too, but instead of a famous book enumerating them, we have a famous blog post stating that functional languages are so awesome that they don't need patterns (or at least, this is how most people seem to interpret it).

I'm sure there is some (very high) level of inherent project complexity where the massive number of abstractions and tools that Spring Boot gives you (and forces on you) actually starts turning into a net positive... And I'm also fairly sure that most projects don't quite break even, and would be better off with something more lightweight.

Currently new AAA titles debut for 60 to 80 USD. I'm wondering what the piracy situation would look like in the USA, if this was, say 160 to 220 USD; because that is what paying US prices feels like to the median person.

I think it's a terrible _interview_ question, partly due to it's "IQ test" nature, but mostly because it's a pretty hard problem and I really wouldn't expect someone to be able to just spew out a solution the first time they hear it.

Of course, the process would be more about the interviewer observing your thought process, seeing how you develop a notation for solving this thing which you almost certainly don't have any pre-existing notation for, etc. I just really wouldn't expect much progress in the space of 5 to 10 minutes, although I am basing this on the "13 marbles" version of the problem.

I see this trope fairly often, i.e. the assumption that an LLM would need to have been trained on . Now, while I do have a moderate amount of background in AI, I am definitely not an expert on LLMs as such. I would be interested to hear someone's take, who does work actively in LLM research. Can they generalise "well enough"? They certainly seem to be able to do so, from my anecdata, and I don't believe "training explicitly for every possible scenario" would have scaled even to today's state.

I don't have a TSC-X, but did frown a little bit that there wasn't a generic support for controllers with plain axes. I have a VKB STECS, and basically a 85% of train sims need a workaround.

The good news: Claude Code threw together a working prototype for me in a few minutes that had me mapping the two axes (power / brakes) perfectly. It's really a low barrier to entry these days. Can confirm that this game is amazing with it.

Novels like these need some life experience to really shine. A 13 year old isn't going to go "how does this writer see so clearly through so many of life's finer details", because they have never experienced 90% of what's being talked about.