Anecdotally Windows ARM works fine for me, although to be honest most of my work is command line + browser anyway. WSL works like a treat. Steam installs and most lower end games also play fine on my ARM laptop too. Games that require kernel anticheat don't work.
I think they make a great "second device" where you have something meatier to fall back to if something doesn't quite work right. I'm not sure if it's ready to take on the "main device" role just yet. But it's a far far better experience than the Surface RT days.
> Also I just find it a little insulting if someone sends me an AI response
I run into this with AI-generated PR comments. I think where I work we are still grappling with the "right point", because LLMs can certainly provide valuable feedback, but they are not at the point where they can do so unsupervised, and to do so just feels unprofessional.
And there's another layer where it is even worse when a colleague spends the time critiquing code and someone (or something) replies to the comment with mostly useless filler. It's like being handed a small hand-crafted gift and then throwing it into the garbage in front of them.
I've come to the opinion that conflicts should be committed and merge fixes should be in another commit afterwards. Arguably even if the merge fix is trivial.
A merge conflict means that some automated tool couldn’t figure it out. But all a merge is is a commit with two parents and an accompanying diff that shows the process of combining them. A merge conflict isn’t really in any way special. It just means whatever algorithm was used couldn’t do it unambiguously without human help.
I'm certain there are a non-zero number of TVs that either attempt to auto-join popular wifi hotspots (xfinity/tmobile/starbucks/etc.) and/or have cellular connections for telemetry.
Thinking more on this I think a business opportunity in the future will be companies that design hardware stacks that can go in random appliances that can gather usage information in the name of telemetry.
I give it +/- 5 years before an OTS coffee maker at walmart phones home.
The premise of this article is incorrect - MS isn't cancelling Claude code internal usage because of AI costs too much, they're cancelling it because GitHub copilot is the compete product and they want their employees to use their product.
It's the same reason Teams got so much attention during lockdown.
Yeah, they conflate Microsoft's actions (which are not about cost) with a random quote from the "vice president of applied deep learning at Nvidia," who says that compute costs more than people on his team -- but his team isn't using LLMs for software development, they're literally a deep learning team that is burning compute in deep learning development ways.
If people would do even a little bit of math, they'd see that Microsoft can't possibly be paying more for AI than for developers: They have about 80K employees in product development roles. Senior developers probably cost them $400K all-in.
Do they have a $32 billion Claude bill? I suspect they do not.
Both things can be right: Claude costing too much and migrating employees to copilot, which hopefully will decrease cost as it owns the product, which will in turn increase usage and feedback.
> It's the same reason Teams got so much attention during lockdown
Not sure I see the parallel with the point you were making
Anecdotally from people I know from MS is that adhoc slack usage was popular up until lockdown, at which point more resources was poured into Teams due to everything going remote and internal slacks were frowned upon.
I see a parallel here where a competitor's product is taking over and MS leaders see it becoming an existential problem and are putting their foot down and pushing internal users to the company's products.
Also if half the company don't even want to use something made by the other half it's a bad look lol
> The first half is a constant flood of footage from the iPhone, the DJI Pocket, the drone, the Nikon Z8, and lately the Ray-Ban Metas too. There's always something being recorded. Every photographer or videographer I know is sitting on the same problem: an archive that grows faster than they can edit it. The second half is why mine never gets touched.
This is your second paragraph but reads awkwardly. You mention two halves in the previous paragraph, so I kind of try to map those two halves to the halves in this paragrpah. But I don't understand what the second half is in this second paragraph.
> Three months ago the lodge's social channels went dark. Not for lack of content; the lodge has years of raw footage across multiple SSDs. The bottleneck was editing time, and my time disappeared. Claude Code with Opus 4.5 (and then 4.6) hit the point in February where you could leave agents running for hours and come back to merged PRs. KaribuKit was going live with its first paying property in the same window. I stopped sleeping properly, started running three or four agents in parallel in the background, and the months when I would have cut reels turned into months when I shipped software instead.
I don't fully understand this paragraph either. Your time disappeared? Into what? Was it the lack of sleep? I don't know what KaribuKit is.
> I asked it out loud: how does the agent know what's in each clip?
Did you? Really?
> Four bugs, four lessons
I've noticed that AI tends to rathole into random things when summarizing a piece of work, so I'm skeptical that these were actually the most four interesting bugs you could have shared.
I would recommend you just remove this section or take the time to actually think about some learnings you had from this project. Syntax errors or missed CLI params are mildly interesting but what makes these four bugs interesting to your readers?
> The actual take
The same criticism here applies. Are these your real takes, or did Claude make these up too?
Some obvious tells to me of things that AI likes to write that humans rarely ever say:
> Both real, both consuming attention.
> Four constraints set the shape:
There's way more than just this (the writing style of nearly the entire post screams Opus 4.7), but that's just what jumped out at me when I started reading your post.
I don't mind you used AI to write this but in the future when you write using AI, take the time to read the entirety of the article and consider the goals of what you want to write and if the AI achieved that. Take out what doesn't belong and make sure that what you have left says things in your voice.
I maintain a part of my team's CD process and I've observed a 30% increase in PR velocity since we started adopting agentic tools but it was a "one-off" increase (as-in, it hasn't continued to increase beyond that since about a half-year ago).
I'm guessing though that there are other improvements in code quality and feature velocity. I've noticed personally that AI is really good at catching smaller things that are easy to miss (e.g., if you ask it to rename fooTheBars it also updates all the relevant comments or enums that you might have missed).
I suspect at some point AI-written code will be eventually artifacts generated build-to-build. The design docs and UI tests are the source and the model follows instructions to generate the product. If you make the models deterministic then model improvements give you code improvements across your entire codebase "for free".
I think they make a great "second device" where you have something meatier to fall back to if something doesn't quite work right. I'm not sure if it's ready to take on the "main device" role just yet. But it's a far far better experience than the Surface RT days.
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