So, it's just a matter of time until they destroy this project in favour of their cloud interests. Such a shame, it is (was) a nice open source project.
Nice in theory, in practice I remember having to support Internet Explorer about 4 years ago. Hard to justify the investment sometimes, at least polyfills gave use some sanity back. The only reason to do it was: Rich old enterprise customer who can't install chrome due to policies created by Dinosaurs.
Websites are surprisingly hard to maintain long term, specially for a broad audience of devices. Developer Experience can lead to better UX, the easier it is to build/maintain, the more likely we're to do it.
Given how bad AI is at design plus all the unstoppable slop train, I expect websites to become much, much worse.
Now game devs can optimised their game for it and Steam Machine will get royal treatment. It's not unusual for a PS5 game to run slow on a PC with much better hardware due to not being optimised. The Nintendo switch is a great example, pretty old hardware but the games run well (for their intended experience).
Many people are complaining about the price but you can bring you entire steam game collection and even use as a PC if you want, I sold my PS5 once it became a useless brick cause Sony prevents you from running Linux.
I think the core issue is not AI itself, it's people.
Right now non-tech people just think AI will do anything they want and are the one in charge of hiring/firing, managing, etc. It's horrible to be a software dev right now, you've to deal with AI and lunatics.
Of course Domain Knowledge is important but, right now it's very hard to have reasonable conversation because... you know... AI this, AI that. I had a customer showing me a Claude vibe coded atrocity trying to convince me it's was a great app, now ask yourself: How are devs even supposed to collaborate with this without going insane? Simple, you can't.
I think most people are not understanding what this kind of laptop will provide.
Before we get local AI, we'll be using hybrid AI.
Running big models locally is unrealistic ($$$$$) but, if you imagine an Agentic Workflow where some bits run on the cloud and other smaller tasks locally, it's an amazing deal. You don't need Opus/Code/DeepSeek/Kimi/etc to do basic stuff that models like Gemma4:12b/Qwen-27b can do locally with much less latency.
Having a laptop where I can use a remote big model and combine it with 5 local domain specific models, is something I would love to do today. Imagine using OpenCode and you've a small model deciding which tasks run locally, then decides if you've a good local model for XYZ task or if we use a cloud model.
My main concern is: Is this hardware powerfull enough to allow local quick models switch? Unlikely but I hope I'm wrong
Discovering vulnerabilities is a highly creative task, it's when you explore unsual paths that you discover atttack angles. Some bugs are simple, other are a complex orchestration of many factors.
By "Working with the model", is essentially reading the ouput of prompts and pointing in a direction just to decide the next steps. You could try to increase the prompt limit and create an agent that explores multiples directions in a DFS manner.
The issue with vulnerabilities is the agent not knowing when to stop because it's hard to validade if you reach the final result or not. I get amazing result when I code with AI, letting the AI go wild is just a waste a time and tokens.
I recommend you to read the write up on the crackme (https://crackmes.one/crackme/698f40f1e2ba6023bfacaa82), I think most experience developers would need, at least, 2 months of learning reverse engineering techiques to hopefully crack this one. GLM 5.1 manage to solve it, it didn't "copy pasted" any answer from it's training data. It did a binary analysis, anti debug patching, patching binaries, debugging memory during runtime etc. It only took about 20 minutes.
After seeing what GLM did, I do believe Anthropic concerns about Mythos are real. Cracking software just became a lot easier, too easy for my taste. Video games cheats will be the norm, cracked desktop apps without licenses and infected with malware. It's not a new thing but it just became too easy.
I've used glm 5.1 on fairly advanced crackme challenges (example: https://crackmes.one/crackme/698f40f1e2ba6023bfacaa82), and to my suprise it was able to patch binaries, doing runtime analysis, bypassing anti debug techniques, etc.
Expecting the model to do everything by itself is unrealistic, I found that working along the modal works really well. I'm not speaking about spoiling the solution, just tell it which direction to explore. Chinese models are much more capable than people give it credit for, but Claude/Codex won the marketing game.
The only usecase of this methodology would be for CI integration, which can be nice but I think security reviews still need human attention and expertise.
I’m using AI to create UIs and I find myself having more time to think about UX rather than CSS. It actually gave me “time” to quickly test design ideas an implement minor details.
I’m actually building better UIs just because it became less time consuming to do so.
There is just a super noisy minority that spams the internet with slop so bad that no one can take their product seriously.
The car front looks ugly to me but, I do remember getting used to car designs that I previously found ugly.
It looks weird/ugly because electric cars no longer need to be longer and have enough space for massive sport engines. Maybe we'll get used to it over time, still I would prefer the front of a Ferrari 458
The interiors look really nice, I'm a fan of the dashboard elements, blending touch with actual physical buttons.
This idea of reviewing an architecture that you never coded is just a fantasy.
At some point in time, me and a lot of people, thought that using Redux was a great idea until we had to manage verbosity and middlewares. Now we had to deal with the consequences of our decisions and we learned.
Today I'm forcing myself to learn SwiftUI and type each character with my hands, there is a part of me asking "Why are you wasting your time instead of prompting it and getting the UI you want in minutes?". Well, even I use AI I must know the domain I'm operating in to create good products instead of useless slop. Even though I've been coding for 20 years now, I still need to be humble to grown in anything new. I can vibecode full apps but I'm not gonna pretend that my experience isn't playing a massive role in guiding the models.
Don't let AI take away your joy for building stuff, it's totally fine not being "productive" and taking your time. Just force yourself to have, at least, 2 AI days off every week.
Guess it really depends on what you use them for. I've been able to built whole apps with them, not slop. Kimi is quite good at design, for 3D, I noticed Gemini 3.1 is excellent for basic to medium use cases.
I've tried both Opus and GPT 5.4, they also hallucinate just like the rest at a much higher cost.
The more you use a model overtime, the better you become with it. It's really hard to measure, my main metric lately has been tokens per second/time to complete task.
At this point I've the feeling frontier models are optimizing for benchmarks and one shot prompts.