Games and other specific applications call for such unidirectional data flow with such massive amounts of "independent" entities. It isn't that it'll catch on or not outside the gaming industry, it is more of a unique solution to a typical gaming problem.
So their are apps that do use similar or ECSs architecture under the hood, it is just more problem related not a solve everything solution.
Not omniscient but I do let them update the system information from one station just because it caused me issues with goal weighing since their information was so limited they almost always chose to stay within a known route versus exploring, this helped giving them more information.
But I did think, one station info per station probably also did not make sense, technology-wise, so I thought expanding it worked.
The faction system was my answer to what makes ships or planets' goals go beyond their immediate needs, and factions came naturally next. They want to make money and shift priorities to do it through incentives. Like subsidies almost.
I was hoping/thinking they (factions) could escalate to blockades, monopolies or just more supply control, skyrocket prices and events combat to hold choke points, blockades or sanctions. That way that agents FSM is focused on those goal oriented actions and ships can focus on their well being plus their factions incentives, and the crews needs handle immediate needs.
I did! I am more familiar with Godot but just ran into performance issues and then switched off their node scene straight to their rendering API, which made me feel like I abandoned Godot at that point. I am sure it could be optimized more but I want to worry less about chucking rendering and more scaling the economy simulation the further it went out, thus the more things to render, the harder it was for Godot.
Bevu/Rust just made it easier to brute force that scaling, since they have smaller footprints (overhead?)for each thread/process spawning.
Meh, we should just ignore that kind of propaganda. We copy things too, we use a system to protect IP because copying is such a normal and strong human thing to do.
In fact, when we don't discuss China, most find modern software patents and copyright to be abusive.
Finally, copying UX standards has been done for ages, it gives users a comfortable way to start using a product and instead of fighting that to be unique, some rather embrace it.
It can be jarring using so many different apps if each one tries too hard to be unique.
And this is my two cents, here it makes sense to have a similar interface, it's ultimately an app with chat sessions.
There seems to be a team sport mentality with AI topic in HN these days. Almost feels like people are picking sides, and thus not being very thoughtful or rational.
Sigh, there definitely an attitude creeping into the community and it's a huge turn off unfortunately.
I'm confused, why are you arguing about this? Stick with YouTube. This isn't for you.
It's even in the name. PeerTube. Peer. Your talking about 'consumers' of a product you produce vs a way to share videos that isn't YouTube with your .. PEERs.
Not 100k views videos. Think you should step back and think what your actually trying to debate or argue. It comes off kinda like your misunderstanding the software and conflating a lot of things that don't relate and not relevant to PeerTube.
It's true, but I see it happening. I’ve watched seniors with 30+ years of experience adopt them successfully without losing their classic rigor.
Personally, I get huge mileage out of LLMs, and yes, I care deeply about code quality, readability, and debuggability.
I've seen juniors absolutely rock with them.
And I've seen the exact opposite, where they just struggle to get good results.
In the end, I think the divide comes down to management experience. The people thriving are the ones who have led teams, especially teams of contractors, which is the best analogy for how you have to interact with an LLM.
Those folks know how to break down problems, provide the right context, and scope a task just enough to see the "contractor" succeed before letting them move forward.
On the other hand, individual contributors who are used to just grinding solo often struggle. They expect a one-shot miracle. They say, "Hey, my code is buggy, fix it." When the LLM inevitably hallucinates or steers them wrong, they give up. The results are completely different based on how you treat the tool.
They might just have a high quality of control and standards that it is hard to find that pattern with the LLMs.
I think fierce individual contributors are a lot more valuable in the era of llms as well. We as humans typically achieve better balance with new stuff when we allow backlash from new processes that start to trample on old ones without understanding AKA the Chester's fence.
I think a better analogy is cartoon or animated films. The artist, creator, engineer lays the key frames, the plot points, characters, etc. The team builds it. Fills in gaps, especially with direct input from the creator.
The creator still gets the credit.
LLMs can just be the part that accelerates laying the code down.
I think folks are just too emotional over a tool that we are ignoring drawing similarities on purpose. That or just different audiences, hackers vs professionals. The latter just meaning being payed and usually working in a team. The styles can be different and the value placed on crafted code vs results.
I thought bringing this article up during the AI era might spark some good discussion.
My thoughts to start:
I read this a while ago, and it shaped how I think about iterating on software. For example, I've been working on an internal tool for several years. While it was immediately useful, it has become significantly more valuable over time as we discovered what features it actually needed, adjusting the roadmap based on real usage, correcting poor assumptions, and working with behavior driven feedback.
Code generation is not the bottleneck of great software. Human discovery is.
Like Joel notes:
"[...] getting good software over the course of 10 years assumes that for at least 8 of those years, you’re getting good feedback from your customers, and good innovations from your competitors that you can copy, and good ideas [...] You have to release early, incomplete versions"
Good software takes ten years to build, and I don't see AI accelerating that timeline. In the end, it's the human in the loop that matters when it comes to refining software over a decade.
AI is a multiplier for the typing part, but the limiting factor of software (especially software built FOR humans) is human bandwidth: the time it takes for users to encounter a pain point, articulate it, and for us to engineer a solution that fits into the system. True innovation is found in the balance between the tool and its users.
Well I've enjoyed making little "flash" like games with AI. I have a SKILL.md for how to build out a pico8 game that it updates when it finishes a game.
I give it an rough idea, or none and have it make a game.
See if there something here you enjoy to convince you I do think AI can slowly as they improve make more variety of lightweight 15 minute games.
I thought modern science doesn't reject anthropomorphism anymore? That's it's more nuanced and that it caused more problems than it helped by rejecting it out right?
I think we were taught anthropomorphism was wrong and that wasn't truly settled.
Anthropomorphism between animals though, not machines.
That's a good point. For me it's getting people to realize they need to take up practice that help minimize these things. It's kinda us and them problem.
We need to ensure we don't just blindly install the latest, patch every CVE by just bumping everything to the latest even if the vulnerability has nothing to do with their system or use of said library.
We should have rules that we install the latest that's older than three days.
We should be running "npm audit" and other stuff like Trivy.
It's the exact same logic people used for Apple computers back in the day. The idea that Macs didn't get viruses because they were inherently more secure.
But that wasn't true. It was purely a numbers game. Windows' popularity was so far off the charts that hackers naturally targeted Windows users instead of Mac users; it was just a better use of their time.
The same thing is happening here. Other package managers do get compromised, but the sheer frequency of npm incidents just reflects how overwhelmingly popular Node.js and web apps are right now. JavaScript simply has a much higher usage rate than most other languages.
That being entirely unfair. It is still a skill. They still learning stuff. It does not help them to be trapped in a bubble. But nothing is not transferrable. Things we learn, even if they are only a React can't write vanilla JS, it's still unfair to say they have no skill.
Just not a correct interpretation. Many skills start that way and even some people make a whole career mastering one thing and one thing only.
Not saying being trapped in React land unable to break out is good. But being able to create something, even if it's just with Nextjs is still a good thing.
We should hate on the businesses that force us to take shortcuts, value quantity over quality. They wanted boot camps with code monkeys.
I've tried these with Claude various times and never get the wrong answer. I don't know why, but I am leaning they have stuff like "memory" turned on and possibly reusing sessions for everything? Only thing I think explains it to me.
If your always messing with the AI it might be making memories and expectations are being set. Or its the randomness. But I turned memories off, I don't like cross chats infecting my conversations context and I at worse it suggested "walk over and see if it is busy, then grab the car when line isn't busy".
So their are apps that do use similar or ECSs architecture under the hood, it is just more problem related not a solve everything solution.