No, they need to ditch drive letters first. The NT kernel and NTFS don't even require them (I used to mount disks without drive letters back in the NT 4 era). They just don't care enough to get rid of this annoyance.

Nobody wants to use \??\GLOBALROOT\Device\HarddiskVolume3\ in their paths.

Nonsense. You can mount filesystems to mount points in much the same way as is done in Unix. No one would ever need to do that.

You can indeed use mount points like C:\mountdir, but that's still on the C drive, which is a drive letter. It's not "no drive letters".

And if \ was an alias for C:\ this would just be \mountdir.

users , especially non-technical, find it highly useful in my experience. Is it a net positive to get rid of them, or will it largely only make developers happier ?

It’s arcane and technical for no reason. /Users/ME/Documents, /Media/MyThumbDrive/…, etc. are much clearer and less confusing than C:\…

At the very least, drive letters do make SMB shares a bit simpler for the non technical folks. T:\MyData is easier for them than \\0010-somehost-win.site1.mycorp.loca\Share01\MyData\

I used to support a group of completely tech illiterate users in construction & manufacturing. Them figuring out T:\ was hard enough, ask them to type in a UNC path into the address bar in explorer and you get "Wtf is file explorer? Wtf is an address bar? Where is the backslash key??"

Then in this hypothetical world you could mount \\0010-somehost.win.site1.mycorp.local\Share01 to /Share01 rather than T:

Or just use sane names like \\MyDivision\Share01\MyData and mount that to \Network\Share01 or some such.

Instruments of justice that are capable of being captured are not instruments of justice at all.

So the law is not an instrument of justice then, right… and thus enforcing the law will do nothing to fix the problem of capitalism, since those with capital have already purchased the law?

This situation brought to you by the billionaires behind Chief “Justice” John Roberts.

Not by the billionaires, but by the Eternal Peasant, who will break a billionaire's head with the same exultant sadism as they would yours or mine.

Discusses the concept of Market Socialism, which is a hybrid system meant to avoid the worst aspects of both Socialist and Capitalist systems, while putting the goal of human fulfillment at its center.

Not sure where 40 tokens per second is coming from. I’ve seen 95-100 tokens per second on M5 Max 128GB running Gemma 4 31B. I’ve done experiments where it is faster than Claude Opus 4.5 for the same prompts.

    > M5 Max 128GB

Wild. That must be like a 5,000 USD laptop.

can you provide your configurations pls ?

It's actually a bit faster than that now it seems, about 112 tok/sec.

Configuration:

Gemma 4 31B Instruct Q6K Context size 40960 LM Studio 0.4.13+1 Metal llama.cpp v2.14.0 LM Studio MLX (Apple M5) v1.6.0

Here are my results:

prompt eval time = 32545.36 ms / 5625 tokens ( 5.79 ms per token, 172.84 tokens per second) eval time = 20227.99 ms / 310 tokens ( 65.25 ms per token, 15.33 tokens per second) total time = 52773.35 ms / 5935 tokens

This was for interacting with a local MCP service, running a tool that returns a ~20KB text file to the agent to add to the chat context.

I'm seeing about the same number of tokens/second on an M2 Ultra that I have access to (also with 128GB of memory).

This is surely apples-to-oranges to the OP results (and I don't spend a great deal of time benchmarking these things, so my methodology might be lacking), but it's interesting seeing okay performance for a top open model. For most use, however, I find Gemma 4 26B A4B (Q6K) to be good enough (esp. for MCP calling) and much much faster (~1,200 tokens/second).

Ultimately, information is a public good: it is non-excludable (you can’t stop people from using it) and it is non-rival (we can all use it at the same time). Public goods are often very useful, and because they are non-excludable and non-rival, ultimately can’t have a market-based business model. I would class open-weights AI models as public goods, and would support government expenditure to produce them.

Calculating hourly costs for these models makes me think that the decision of when to hire an SWE vs. increase use of AI may follow a similar pattern to the decision to use cloud compute vs. on-premises. I don’t cost $120/hr (incl. fringe), but my employer pays my salary all year long, no matter if I am working or on vacation. Whereas if they use an AI model to do the same work, they may be happy to pay $120/hr or more, since they may only use the model for a small fraction of 2080 hours per year, so they’d still save money, and not have a messy human to deal with.

The framing of AI vs SWE cost assumes you know what the AI is actually spending. Most teams don't. They see a monthly total, not per-agent/per-step attribution. The decision math only works if both sides of the equation are real numbers. That is the gap Traeco closes. traeco.dev

The framing of AI vs SWE cost assumes you know what the AI is actually spending. Most teams do not. They see a monthly total, not per-agent/per-step attribution. The decision math only works if both sides of the equation are real numbers. That is the gap Traeco closes. traeco.dev

I remain convinced we won’t look at project estimates as time based in software engineering as our primary cost estimate. And this is transition will happen rapidly. We’re going to shift to a capex/token spend model for project estimates where the business will say “ok I do want that feature for $1000 in tokens”.

I agree with you directionally that project estimates are/will be affected by this but I don't see a scenario in which time is completely removed from the equation with respects to projects & estimates to execute on them. We're all constrained by time, finite resource. It's always a factor in business.

I would be very surprised if they can scale hiring contractors to reliably renovate buildings.

If you start buying minis, then you need to house, power, and cool them. So you are building a mini data center. If you are building a small data center, economies of scale will drive you to want to build larger and larger. However, this gets expensive and neighbors tend to not like data centers (for good reason). To me this seems like asymmetric warfare against hyper-scalers.

Yup. This way, the people pay for the air conditioning themselves and they probably don't even notice the extra cost.

& if they live in a cool place, they're getting a small space heater as a bonus.

I recently stopped using Backblaze after a decade because it was using over 20GB of RAM on my machine. I also realized that I mostly wanted it for backing up old archival data that doesn’t change ever really. So I created a B2 bucket and uploaded a .tar.xz file.

I’ve recently switched from Minio and Localstack to Garage. For my needs (local testing) Garage seems to be fine. It’s a bit more heavyweight and capable than I need now, but I like that it may give me the option of having an on-premises alternative to S3-compatible stores hosted in the cloud. The bootstrapping is a pain in the ass (having to assign nodes to storage and gateway roles, applying the new roles, etc). It would be great to be able to bootstrap at least a simple config using environment variables. However, now that I have figured out the quirks of bootstrapping, it just works (so far; again, I’m not doing anything complicated).