ghrl

169 karmajoined 2 года назад

comments

5 дней назадdiscuss

What shines through here is that the AI writing / reasoning this is about as lazy as always, declaring a hard limitation where some engineering might solve or work around the limitations. In modern JavaScript a surprising amount of tasks can be handled, e.g. with Workers and in a streaming way.

14 дней назадdiscuss

Beer CSS is great. I've used it for multiple simple projects and it provides a great DX with the clean html code and the many snippets on the official website. The only downside is that LLMs are quite bad at working with it from my experience, maybe it's just too simple for them..

29 дней назадdiscuss

That's refreshingly usable and not-slop-looking, nice additional style.

29 дней назадdiscuss

Yeah, spot on. I had an agent delete some files it shouldn't have as well, similarly to me making the same mistake. I think system prompts should default to using `trash` over `rm`. For now that's just in my AGENTS.md, and gets honored most of the time.

29 дней назадdiscuss

Sounds like a case for NixOS

29 дней назадdiscuss

Amazing observation, and I'm certainly guilty of it too, but it is just way too convenient not to sandbox it, and some tasks right away depend on not being sandboxed.

For anything other than writing code directly in a fully contained git project, where sandboxing might work well, it requires access to system wide tools, user configuration and more.

Occasionally I tell the agent to do everything inside of docker, which works too and it leaves the system alone then mostly, but adds significant overhead and slightly degraded perceived quality / effectiveness.

I think the most important takeaways are to have reliable backup strategies, access control and security mechanisms, which is a win regardless. Whether by the agent or the human, mistakes happen (like a rm -rf * ran in the wrong directory), and where they would be devastating, there should be other protections than just "hope it won't happen" or "rely on a sandbox to prevent agent error".

29 дней назадdiscuss

I would assume that cost to be minimal, considering their PR never got merged. And if it were me I would consider that well worth the entertainment.

30 дней назадdiscuss

Or by using a proxy, yeah. Personally I would still prefer a multi provider harness over CC when using it with another provider, if alone for the visible reasoning, model switcher, cost estimation and so on. So far I've only preferred CC when I needed to work with Jupyter Notebooks because it has built-in tools for that.

30 дней назадdiscuss

In many cases they're amazing, too. And the visible reasoning and the pricing are amazing too.

в прошлом месяцеdiscuss

Yeah, I used that too on my last Mac. But the page explicitly states the benefits of this approach (preventing it from launching all together without doing anything vs listening for the launch and killing it). It also does not use a menu bar icon, which is also good considering the limited space.

в прошлом месяцеdiscuss

Yes, certainly. I've heard of people that let an agent run on one machine, point a USB Camera at the target and give the agent ssh access and something like imgsnap (cli webcam command) and then let it run autonomously. The agent can then try all sorts of things and also verify the results without asking the user. I think that's quite a good workflow, giving at least a basic feedback loop for work that can't be tested with just software.

в прошлом месяцеdiscuss

I would say if it's only used as the build and publishing device and development happens elsewhere, this would work without problems. 8Gb for building the iOS app and testing on a real device or even an emulator would likely work. Apple's swap is also quite fast.

в прошлом месяцеdiscuss

I was thinking all that too and considering commenting about being sick of those credit card size claims, but after seeing the footage I am genuinely impressed. Great work there.

в прошлом месяцеdiscuss

Wow, very interesting example.

в прошлом месяцеdiscuss

I believe you can get close to that with various Instagram mods for Android. They have advanced features like only show posts from followers and stuff like that. I switched to one of them after realizing the 5 second ad breaks I got were only there because I disabled personalized advertising.

в прошлом месяцеdiscuss

I would disagree. Having all the messages locally and sending them with the request means you can switch inference providers or even models mid-conversation. It also means that the provider doesn't store the entire context, which often contains massive parts of proprietary codebases, secrets and PII and instead the agent harness manages all that. While a simple `continue thread` API field might seem more convenient, the cost is still determined by the input token count and cache rate, so it just abstracts this crucial implementation detail away.

в прошлом месяцеdiscuss

I am mostly using OpenCode and barely ever see a permission prompt. While they do enforce it for outside workspace read/write, with the bash tool the agent can just bypass that. I'm not quite sure why it is that way, and it certainly isn't a very good solution, but likely not worse than asking for everything which just trains the user to always accept and provides a false sense of security then.

в прошлом месяцеdiscuss

I don't quite understand the benefit of the setup. If there are legacy IoT devices that need unique named 2.4G network, just broadcast another SSID for them. So each router broadcasts main 5G (common name, fast roam etc), main 2.4G (same as above) and legacy IoT 2.4G (with a different name for each AP, and possibly worse encryption and maybe even TKIP). That wouldn't hold back the network for legacy devices.

2 месяца назадdiscuss

I would say that is highly unlikely if by SOTA models you are not just referring to coding benchmarks but more general purpose ability and domain-specific knowledge. For example Kimi 2.6, which is comparable to Opus 4.6, is roughly 500+GB large, and I don't see how that would run on consumer hardware anytime soon. Besides, this is not just about the technical feasibility, but also economically not viable whatsoever. Why should consumer laptops be capable of running such models, when they would be massively underutilized most of the time, when inference providers can produce the same results faster, cheaper and a lot more viable economically?

2 месяца назадdiscuss

Something MacOS and Windows support natively would be a good start, it could grow from there.