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Three facts to consider:

1. CLAUDE.md is not part of the system prompt

2. The Claude Code system prompt almost certainly gives directions about how to deal with MCP tools, and may also include the list of tools

3. Instruction adherence is higher when the instructions are placed in the system prompt

If you put these three facts together then it’s quite likely that Claude Code usage of a particular tool (in the generic sense) is higher as an MCP server than as a CLI command.

But why let this be a limitation? Make an MCP server that calls your bash commands. Claude Code will happily vibe code this for you, if you don’t switch to a coding tool that gives better direct control of your system prompt.


>is higher as an MCP server than as a CLI command.

What do you mean by "higher"?


An 14-inch M4 Max Macbook Pro with 128GB of RAM has a list price of $4700 or so and twice the memory bandwidth.

For inference decode the bandwidth is the main limitation so if running LLMs is your use case you should probably get a Mac instead.


Why Macbook Pro? Isn't Mac Studio is a lot cheaper and the right one to compare with DGX Spark?


I think the idea is that instead of spending an additional $4000 on external hardware, you can just buy one thing (your main work machine) and call it a day. Also, the Mac Studio isn’t that much cheaper at that price point.


> Also, the Mac Studio isn’t that much cheaper at that price point.

In the list price, it's 1000 USD cheaper. 3,699 vs 4,699 I know a lot can be relative but that's a lot for me for sure.


Fair. I looked it up just yesterday so I though I knew the prices from memory, but apparently I mixed something up.


Being able to leave the thing at home and access it anywhere is a feature, not a bug.

The Mac Studio is a more appropriate comparison. There is not yet a DGX laptop, though.


> Being able to leave the thing at home and access it anywhere is a feature, not a bug.

I can do that with a laptop too. And with a dedicated GPU. Or a blade in a data center. I though the feature of the DGX was that you can throw it in a backpack.


The DGX is clearly a desktop system. Sure, it's luggable. But the point is, it's not a laptop.


How are you spending $4000 on a screen and a keyboard?


You're not going to use the DGX as your main machine, so you'll need another computer. Sure, not a $4000 one, but you'll want at least some performance, so it'll be another $1000-$2000.


> You're not going to use the DGX as your main machine

Why not?


Because Nvidia is incredibly slow with kernel updates and you are lucky if you get them at all after just two years. I am curious if they will update these machines for longer than their older dgx like hardware.


I didn't think of it ;)

Now that you bring it up, the M3 ultra Mac Studio goes up to 512GB for about a $10k config with around 850 GB/s bandwidth, for those who "need" a near frontier large model. I think 4x the RAM is not quite worth more than doubling the price, especially if MoE support gets better, but it's interesting that you can get a Deepseek R1 quant running on prosumer hardware.


People may prefer running in environments that match their target production environment, so macOS is out of the question.


The Ubuntu that NVIDIA ship is not stock. They seem to be moving towards using stock Ubuntu but it’s not there yet.

Running some other distro on this device is likely to require quite some effort.


I think the 'environment' here is CUDA; the OS running on the small co-processor you use to buffer some IO is irrelevant.


It still is more of a Linux distribution than macOS will ever be, UNIX != Linux.


It's a hoop to jump through, but I'd recommend checking out Apple's container/containerization services which help accomplish just that.

https://github.com/apple/containerization/


You're likely still targeting Nvidia's stack for LLMs and Linux's containers on MacOS won't help you there.


The platter is a circle so using the uniform distribution [0, 1] is incorrect, you should use the unit circular distribution of [0, 2pi] and also since the platter also spins in a single direction the distance is only computed going one way around (if target is right before current, it's one full spin).

But you can simplify this problem down and ask: with no loss of generality, if your starting point is always 0 degrees, how many degrees clockwise is a random point on average, if the target is uniformly distributed?

Since 0-180 has the same arc length as 180-360 then the average distance is 180 degrees. So average half-platter seek is half of the full-platter seek.


What you wrote only applies to rotational latency, not seek latency. The seek latency is the time it takes for the head to reach the target. Heads only rotate within the small range like [ 0 .. 25° ], they are designed for rapid movements in either direction.


> If you're copying and pasting something, there probably isn't a good reason for that.

I would embrace copying and pasting for functionality that I want to be identical in two places right now, but I’m not sure ought to be identical in the future.


I agree completely. DRY shouldn't be a compression algorithm.

If two countries happen to calculate some tax in the same way at a particular time, I'm still going to keep those functions separate, because the rules are made by two different parliaments idependently of each other.

Referring to the same function would simply be an incorrect abstraction. It would suggest that one tax calculation should change whenever the other changes.

If, on the other hand, both countries were referring to a common international standard then I would use a shared function to mirror the reference/dependency that they decided to put into their respective laws.


If you're going to be using USB drives anyway, then using them to move files into the country would be faster.


More dangerous though. You'd need something like truecrypt, too.


btw, veracrypt is the name if the follow up project. truecrypt shut down over a decade ago rather abruptly, so anything labeled truecrypt today is suspect as either out of date or potential malware.


Wasn't the conspiracy theory that truecrypt got shut down because it was 'too effective', and the successor projects presumably have intentional backdoors or something?


Truecrypt was likely developed by only 1 man, Paul le roux, who likely shut it down because he was on the run for being an international drug/human smuggler/cartel member. It’s kind of a crazy story.

But either way both truecrypt and veracrypt were independently audited and no major flaws were found. Not sure when the last veracrypt audit was done.


Nah, just drop a few thousand 1GB flash drives from a plane. Load them with a tor browser, a wireguard client, and instructions on finding a remote exit. Only one copy needs to survive and it can spread very quickly and irreversibly by foot.


Yeah, this is a great approach if you're already at war with a country.

If you're not and they're still allowing your planes to fly through their airspace then this is a great way to ensure that they lock your (and your friends') planes out.


Drop them from commercial planes via the toilet?


When you flush the toilet in an airplane the contents is normally vacuumed in to a holding tank which gets emptied after the plane lands.


Then why have people died from getting hit by frozen pee icicles?


pretty sure that's never happened, it's an urban legend


Plugging in a strange USB drive?

What could go wrong.


Would you like a short list, a long list or ...


Typescript ecosystem calls these "branded types" (branded like cattle, presumably) which I found to be a good evocative name.


It's unjust in the same sense that some people complain about capitalism being unjust: some people are wealthy who didn't cosmically deserve it, but just got lucky. There is disagreement over in which way they were lucky (random luck, or lucky to have the right parents, education, genes, etc.)


> Being in contact with reality can be actively harmful to reproductive fitness if it leads you to, say, decide not to have kids because you are pessimistic about the future.

The fact that you can write this sentence, consider it to be true, and yet still hold in your head the idea that the future might be bad but it's still important to have children suggests that "contact with reality" is not a curse.


If you can define your problem well then you can write tests up front. An ML person would call tests a "verifier". Verifiers let you pump compute into finding solutions.


I'm not sure we write good tests for this because we assume some kind of logic involved here. If you set a human to task to write a procedure to send a 'forgot password' email, I can be reasonably sure there's a limited number of things a human would do with the provided email address, because it takes time and effort to do more than you should.

However with an LLM I'm not so sure. So how will you write a test to validate this is done but also guarantee it doesn't add the email to a blacklist? A whitelist? A list of admin emails? Or the tens of other things you can do with an email within your system?


Will people be willing to make their full time job writing tests?


We’ll just have an LLM write the tests.

Now we can work on our passion projects and everything will just be LLMs talking to LLMs.


I hope sarcasm.


They probably won't. But it doesn't matter. Ultimately, we'll all end up doing manual labor, because that is the only thing we can do that the machines aren't already doing better than us, or about to be doing better than us. Such is the natural order of things.

By manual labor I specifically mean the kind where you have to mix precision with power, on the fly, in arbitrary terrain, where each task is effectively one-off. So not even making things - everything made at scale will be done in automated factories/workshops. Think constructing and maintaining those factories, in the "crawling down tight pipes with scewdriver in your teeth" sense.

And that's only mid-term; robotics may be lagging behind AI now, but it will eventually catch up.


As well, just because it pasts a test doesn't mean it doesn't do wonky, non-performant stuff. Or worse, side effects no one verified. Plenty often the LLM output will add new fields I didn't ask it to change as one example.


> by the time I write an exact detailed step-by-step prompt for them, I could have written the code by hand

The improved prompt or project documentation guides every future line of code written, whether by a human or an AI. It pays dividends for any long term project.

> Like there is a reason we are not using fuzzy human language in math/coding

Math proofs are mostly in English.


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