I used it to try it out. Security wise I don't trust it at all so I had it running in a VM and local models.

It was able to create an application that Claude created, using the same instructions file. Considerably slower but I was surprised it could do it.

I used it initially. It was great and useful but the api costs were pretty high..

Now, I use claude code directly on my machine with the remote control flag.. so its like open claw exactly. I can be outside and give commands to it via mobile app

I've been using it since about February, still using it. It's running on my old M1 MBP. I have a lot of automations on OpenClaw, things like "Every week summarize this data and send me a message about it" or "check when a new version of an NPM package comes out and submit a PR to update it."

It's quite expensive from a value per token perspective. It's quite cheap from a "send one message from my phone and it does something probably productive" perspective. No major security breaches yet.

if you're one of those enterprises it's perfectly reasonable to assume you're more likely to go have your procurement and legal teams negotiate with google for one of those weird boxes to run gemini on prem (https://cloud.google.com/blog/products/ai-machine-learning/r...) or other enterprise-y nonsense vs buying consumer hardware to run a chinese large language model in your network. I do not envy the person at a company having to get approval model by model because of weird open source licensing terms dealing with the "how do we know chinese models are safe" question (hopefully they're at least getting asked in the context of hooking it into an agent harness so there's some sort of plausible risk that necessitates the conversation - i can very much imagine it getting shut down to even run in a sandbox because chinese model + people being scared after the huggingface stuff). There's a lot of reasons to assume enterprise wouldn't be interested, and it's very very cool that they are IMO. Anthropic cut claude code rate limits - they dont seem to be see open source llms as a market threat (rhtetoric to the white house aside) yet but enterprises being willing to run consumer hardware to run local models could make things a bit more tangible

> The target audience didn't evaluate that as a limitation - the majority of the market for Apple devices does trust that they will not produce and sell a computer incapable of support their use.

Well, kinda the point. We know this to be fully true in retrospect (and many people correctly predicted it) but decent arguments existed against it at time of release.

>"the majority of the market for Apple devices does trust that they will not produce and sell a computer incapable of support their use"

the problem with that argument is that the vision pro exists, where they clearly overestimated demand, and where even among people with interest in VR and disposable income, the compromises on battery life and weight were actually too much to bear. Forecasting is just hard and you always need to be especially skeptical when you yourself are doing the forecasting for something you want to succeed. All those arguments for the neo line up in retrospect hindsight is always 2020

I am also willing to overpay to not be reliant on cloud things, to have control of local hardware.

My biggest problem with buying a Mac Studio is that even in the case of the M5 Max models, I can’t think of any non-AI macOS applications in my creative life that have anywhere near that level of hardware needs, and nor can I forecast that I would within its ordinary supported lifespan as a macOS machine. These machines left high-end stills and modest video work behind generations ago, for example.

So while I would like a local machine that I can leave running in a way that I wouldn’t want to do with my old secondhand M1 Max laptop, it’s going to have to be something a little more pragmatic. Probably based around the Radeon R9700, since the AMD/Nvidia gap for LLMs is beginning to close, and even a single R9700 runs the main models I am interested in at speeds that are acceptably faster than what I have here.