benrutter

> The one kind of physical shop I really miss is the kind of place where you can buy one screw, nail or picture hook etc.

So much agreement! I have a bunch of obscure parts like 99 wooden dowels from when I needed one and had to buy 100.

Screwfix is sometimes OK for this, but I still end up in situations like the above where I have 99 wooden dowels that will remain in my garage for all time.

(For what it's worth, I also completely agree with Amazon vs stores like John Lewis etc, I haven't bought anything from Amazon for years now, and definitely don't miss it at all)

> I'd rather read some well written LLM text over some poorly written human effort

I think it depends a bit what's meant by "poorly" but I don't think I share that preference at all.

I would 100% rather read a developers copy explaining why they wanted to build something and what they think is useful about it, even if it isn't particularly polished.

As a comparison, LLM generated "marketing schlock" is polished, but it's normally pretty empty and doesn't convey much of it's value.

As an example, I use lazygit (a TUI git interface) - at least at the time I looked at it, the main intro was a youtube video of the developer talking through the features. It wasn't polished at all, but it did a great job of convincing me that lazygit was a project with a lot of love and thought put into it.

I'm really curious how other codeforges are faring. I only use codeberg and github - codeberg seems to have less outages, especially for a much smaller organisation, but they've recently removed support for LLM projects which could be linked.

Anyone here have data on whether the likes of gitlab have been impacted in the same was as github?

> The article rests on the claim that water usage of data centers on continent X threaten water availability for humans on continent Y.

I don't want to start too much of an off-topic thread within an already off-topic thread, but this isn't a particularly charitable reading. The article itself is mostly laying out information around data centres' resource usage with little prediction for how things would play out. I think statements like:

> The water footprint is equivalent to the minimum annual domestic water needs of roughly 500,000 people in Sub-Saharan Africa

Are clearly just intended as illustrative, rather than a claim that 500,000 people in Sub-Sarah Africa will go without water as a result of AI data centres.

I think the articles head isn't particular good, but it's a fairly moderate take and it's closing message isn't an "AI dooms natural resources" one at all:

> AI within planetary limits is achievable. The report’s central argument is constructive. Capability and stewardship can grow together, but only with measurement, transparency, and shared responsibility across the ecosystem.

At any rate, I definitely don't see any reason this article should be flagged? There's obviously criticisms you can make of it, but that's true of almost any opinion piece that finds itself on the front page here.

It gets a little weird when you start thinking of AI like that, because AI is very corporately based in the US and China, but not as heavily that when from a talent position.

Demis Hassabis and Google's Deep Mind are all British in terms of location/talent, but they certainly aren't from a coorporate perspective (Deep Mind work might happen in London, but it is owned by Google, as US company)

(I don't know a lot about nuclear/aerospace industries, I'm guessing there more location centered just in virtue of being based around physical things, but I could be wrong)

This is a great article, I feel like I think of this a lot when I build something new.

The tricky bit I think though, is deciding what actually is boring, since really we should factor complexity in too.

I work a lot with data in python, for in memory data, the most popular choices are:

- pandas - pyspark - polars

Pandas is the most established, although has a lot of technical limitations, as well as complexities.

Pyspark is definitely an "industry standard" choice, but now you're dealing with distributed computing when you probably didn't need too.

Polars is the simplest in terms of API and not being distributed, but then is the newest.

I can easily imagine a discussion where three engineers all agree that they should choose the "most boring" tech, but all choose a different option.

I'm really interested by what notifications people have toggled. I only ever have text messages and whatsapp (urgh, I know!) enabled and don't get a huge amount of notifications during the day to distract me.

Do other people have more notifications enabled? More friends messaging them? Or just a lower threshold for what counts as too many?

That sounds like a cool project! Did you write it up anywhere at all? (or have any plans to?)

Yeah, I agree - I think smart watches haven't yet evolved out of just being a fun tech gadget. If you just want a timer, I'd recommend just getting a cheap digital watch - you can get a casio for like 20 euros/dollars/pounds/etc and it'll give you a timer and the time/date and not much else. No cool tech gadget, but it 'll stay charged for 10 years rather than 2 days.

To give him credit, it's amazing that Mark Zuckerberg managed to take an easily defensible position like "we shouldn't allow AI to be owned by a couple of tech monopolies" and still manage to find so many individual points and arguments to be completely clueless on.

My personal favourite:

> Before the industrial revolution, 90% of people were farmers growing food to survive. Advances in technology steadily freed much of humanity to focus less on subsistence and more on the pursuits we choose.

Over a long enough time span, the industrial revolution has certainly improved living standards but the industrial revolution itself was l, for many, an absolutely horrific time to live. Life expectancies in cities plumetted and we saw the birth of workhouses.

It's such an odd example to choose for trying to suggest "technology x will help everyone in a non-complicated way". He might as well have picked the atomic bomb.

I like that theory, if I was going to counter it though, I'd say that I'm not sure those features match what language users talk about. For instance:

- C: Users often praise the simplicity of the language

- C++: Users often praise (not always praise?) the large feature set for a low level language

- Python: Folks talk a lot about "batteries included". Although in all honesty, I think having good interaction with other low-level languages is Python's secret feature.

- Java: Really leans in hard to object oriented programming

- JavaScript: Haha, you have to use it!

Not sure I'm really disagreeing with you though, but I think Java promoted its portability much more than it's ever been used (obviously there are cases like Spark which uses the JVM portability).

> In general, I don't think you can argue definitively on the uselessness of a piece of knowledge from a standpoint of ignorance of that knowledge.

I agree, I think those things are definitely worthwhile learning. But I don't think that it follows we should test for them in interviews.

It sounds like you've done some pretty impressive work around graph algorithms, but if a job doesn't need you to do this, testing for it is a little silly. (If it's a criteria you're explicitly hiring for, I think that's clearly different)

Not OP but yes if you consume more jam (not if you consume the same over a period of time, because you're then just paying less for jam over a wider time scale).

The example I've heard given is accounting and spreadsheets. It made accountancy cheaper, but people then started asking more questions and analysis became a thing.

Rather than just taking the reduced spend as profit, companies wound up increasing their accountancy spend overall.

Anyone have info on if other platforms are seeing the same scaling? And if so, are they seeing problems too? I definitely only hear about GitHub outages, but it is a lot bigger than the others.

Those kind of abstract CS interview questions never feel that helpful to me, but in all honesty, your story sounds like a job of the interview working.

You were able to demonstrate that you were enthusiastic and knowledge about programming as a whole, which is probably more helpful than what they were originally trying to test for.

Tangent, but I have a theory that refactoring is one of the best symptoms of a healthy dev team.

It's partly that refactors themselves have benefits, but I think more that the benefits to refactoring aren't visible to something like product-owners, feature tickets, etc.

If teams are refactoring to ensure the health of the overall software, it's a tell-tale sign that developers are happy making recommendations for good software, and that those recommendations are being taken seriously.

I think Martin Folwer might have actually coined the term "software rot" - either way, as an issue it happens most severely when a team either aren't motivated or empowered to build their vision of high quality software. When a team can follow their judgement of excellence, that's usually a great sign!

(and yes, obviously this can go to far, there are probably some teams who rewrote all their stuff in Ruby then Node then Rust and now something else to be "agent native", but in the coorporate world, I see a lot less of this than teams who just don't feel like they have permission to improve things)

> Opposing fascism supported on dehumanizing policies such as racial supremacy is not a mere difference in opinion, as is pushes to invade and annex other countries.

I'm not sure, I'd say two things:

- I think "mere difference of opinion" suggests disagreements can't be on serious issues, as if there's something trivial about "x things racism is acceptable a y doesn't". I don't know that I'd agree? Differences in opinion can be on major issues and are important. - Pushing to invade and annex countries is a real thing, which I said in my comment above, I don't know that interferences like Vance in Hungary are pushing to invade countries though? Other things the US doss might be, but I'm not sure it comes into play here?

> You have both US governments and US oligarchs openly pushing and directly promoting fascist and extremist political parties, while at the same time threatening with annexation and military interventions.

I think the first part of this is political alignment right? What are "fascist and extremist political parties" is not politics with a very different alignment?

I think your second point is a really good one though, the Barack Obama and J D Vance examples are both soft power usage. But in the case of Vance, it comes alongside a state using military force to bully its way through issues, that's a very significant context difference I didn't really acknowledge earlier.

As a UK citizen, it's interesting to think back to Barack Obama's attempt to convince the country not to vote for Brexit (saying the UK would "go to the back of the line" for future trade deal negotiations).

I think the real difference now, isn't so much that the US is applying more pressure on european politics, but that it's politics is so much further away from most european countries than even five years ago.

The importance of trading blocks (as in Obama's example) is a pretty standard view. The support for antidemocratic strongmen (with Vance's support of Orban) is a lot less, even now.

I'd be cautious describing market sell offs as good news for anyone since the fall out could be pretty bad (that's a "worst case" scenario, so far nothing like that)

There's some winners though, people dumping AI stocks are mostly buying stocks elsewhere, Apple being an obvious winner[0].

[0] https://www.theguardian.com/technology/2026/jul/28/apple-sec...

I agree that'd be good long term, like the dot com crash. But I wouldn't write off the short term negatives either- the dot com crash was not fun for a lot or people, an AI crash isn't set to be a blast either.

It probably depends on how people interpret it right? I doubt anyone is saying "I love being tracked" - but some people might choose personalized ads over anonymous ones.

I don't really use youtube natively a lot anymore, but I used to with Google's "personalised ads" turned off. I don't know if you've tried that, but the ads Google serves you if you opt out of personalised adds are sketchy, creepy and mostly not child appropriate (a lot of medical stuff, plus adverts for mail order brides etc). Back then I opted in to personalised ads because being tracked seemed a better option to me than being served inappropriate material without my consent.

Anyway, that's a long rant, but my point is, there's edge-cases and weird contexts in which I can imagine people saying something like "of the options I see as likely to happen, I'd most like to be tracked".

Yup! Not affiliated in anyway, just a fan. I like jupyter but marimo's my go to for a few reasons:

- Automatic reactivity can be turned on (will trigger dependent cells if you uptade an upstream one) - Much nicer non-json file format (just python files, with a seperate output) - Much better virtual environment integration / managent (this is always a hassle with jupyter) - Widgets are great! - Better LLM integration (new marimo-pair means llm can inspect the actual python runtime objects) - It generally "looks" a lot nicer if you're using the web ui, which is nice.

Simple but pretty common use case: If you're ever looking at some pre-existing code and thinking "I don't really get why it's written like this?", you can get a lot out of looking through the git blame/history.

Often "weird design" is there for historic reasons around stuff like backwards compatibility. If your project has a well managed commit log, you can find the notes of whoever implemented it, possibly even with their motivation for doing so.

At the very least, you can find out who wrote that code and ask them about it.

There's a tonne of data in git histories - this article was shared a few months back and is an awesome example of some things you can do with git history: https://piechowski.io/post/git-commands-before-reading-code/

I think 5 years ago, we'd just have thought this was a "badly designed menu" and moved on, but now AI has taught us to feel a deep sense of disappointment with it's particular blend of poor personality-less design.

I was looking at the documentation for cruft the other day and it's mascot is absolutely glorious. Not because it displays any semblance of "good taste", but just because it is the polar opposite of AI generated blandness[0].

Who knows - maybe in the future we'll start embracing signals of human amateurishness and ms-paint created menus filled with comic sans will take off.

[0] https://cruft.github.io/cruft/

> Miss sized models plan out each requirement, and smaller models implement a tightly detailed task? Isn't this the standard approach?

It is, but the article is suggesting something different. The central idea is to use /prewalk to load slightly edited context from the more expensive model into the one, so that the cheaper model doesn't burn tokens reading all the files again.

I can't tell if you're being serious, but if so, this is a bit silly. It feels like saying Covid 19 was no big thing because the Black Death of the 1300s was much worse.

But even more so than that, your own wikipedia article seems to fly in the face of your point:

> Estimated annual temperatures in 1540 were by far the highest between 1500 and 2000, while estimated precipitation was by far the lowest registered until 2025

The weather events we're seeing now are even more extreme that those of 1540, but the impact hasn't been as severe because our food and water supply chains are more resilient.

I loved this article! Regardless of how you feel about AI as an industry or tool, the economics of AI is fascinating. It's awesome to see something like this that gets into the business side a bit more.

I don't know if I agreed totally with the assessment of the risk Chinese labs pose to US labs though, in particular I think the main part I wasn't sure about was this:

> I highly doubt that Chinese models are cheaper to serve on a marginal cost basis, they just seem cheaper because Anthropic and OpenAI are so supply constrained that they are charging far more than they would if there were sufficient supply to meet the demand for intelligence.

How true is this? My understanding from Deepseek's original paper was that they focused heavily on optimising training and inference costs, in particular so that they can operate on cheaper (and more accessible to China) hardware.

It's possible I'm just not in the loop, but nobody seems to talk about US models innovating in this way (I'm just talking about cost-to-serve/train, not saying US AI companies don't innovate in other ways).

It seems to me at least, like there's a fair bit of evidence that AI shifting to a price based commodity market (vs a "best-model takes all" type market) would put China at a significant advantage? And even more significantly, require a pretty hefty correction of company valuations in the US?

> historically we didn’t have LLMs which don’t mind “unpleasant[ness]” and “heavy rework”.

I'm not quite as optimistic. "Unpleasantness" might sound like subjective disgust, but it often relates to objective criteria like complexity, that increases the surface area open to bugs in a real way. Similarly, if reworking has a non-0 chance of bugs, its gonna have some form of risk, and a major one will of course be higher.

LLMs may be capable of a lot, and they miggt change what projects people can take on, but they definitely don't write bug free code.

The bun rewrite/transpile did use some neat ideas like lots of testing and per-file translations, so hopefully they have more in their toolbox than "LLMs hopefully won't be affected by complexity or write bugs"

If you're looking for a non-ghostty recommendation (not that I have anything against ghostty) I use alacritty + zellij and it works fantastic. It doesn't seem to impact battery, I certainly get good battery usage on both my work and home laptops.