davnicwil

I agree and I think the most concrete demonstration of this for me is actually the current air.

It's basically the idea of the pro of 10 years ago but realised flawlessly, and improved upon actually in most ways, for significantly cheaper.

To do this they had to become an execution machine at huge scale to own and solve every piece that held them back in that pro design, and they did, and it's honestly amazing how it all came together.

I think there's a ton of examples where this is true for lower level stuff like open source where you see the internals.

For commerical products it certainly exists too, for example in those cases where you know the product is built by one person or a small group of people who you absolutely know take extraordinary care to get all the details right, and it shows through as a really nice intangible feeling when you're using the product.

That (kind of rare to be honest) 'oh this is just really well done' feeling.

> Most people I know cite +20%-40% velocity

Seems roughly right, that does seem to be about the boost in the most well-suited cases where you essentially know exactly how to solve the problem, the problem won't change much, and it's truly a matter of just churning out the implementation.

In that case precisely prompting, doing the review & nudge loop, can be a pretty nice (nice, still not game changing) speed boost over literally typing out the code to match the design in your head.

The less optimistic view though is that most things you build aren't like that. Even if they seem like it first. These things get booked as a nice speed boost, but you'll only find out much later they weren't.

A confounding factor is that it seems like many people not in the detail of building software do seem to think of most to all things are like that, even before AI assisted coding. Not much need to say more - see the entire history of the 'agile' movement for evidence of this.

And because most things aren't like that, I actually struggle to see fundamentally how more than 20-40% will ever be achieved (short of the ever-present deus ex machina of AGI argument), simply because the generation is already really good for these types of things. So since things like this aren't going to increase in overall proportion of things to be done, I don't see where the overall extra gains come from by models improving at this point.

I think unfortunately it's not about what seems obvious, or even what seems more likely, but about what seems retrospectively justifiable regardless of outcome.

The incentive structure of this type of decision is 'absolutely under no circumstances existentially mess up'. Ostensibly with respect to the organisation, but in actual reality much more so with respect to the individual(s) involved in the decision.

If everyone else is doing something that kind of obviously makes no sense, and you decide to break from the crowd by instead doing what does make sense, then there's a pretty solid chance of gaining a temporary edge while reality resolves the truth. But those gains probably won't matter all that much for the organisation, or indeed your position within it. It's a solid chance of an unimportant gain.

However on the other hand, there's a tail risk that something very unexpected happens and the thing everyone's doing that makes no sense actually turns out to make sense - sometimes even for entirely unpredictable incidental reasons - and then, well, you're in trouble. Not necessarily 'you' the organisation.. they'll likely be able to catch up and it won't matter that much. But for 'you' personally, the decision maker, it's very much not good.

As a bonus, in the much more likely scenario that the thing that makes no sense turns out to indeed make no sense, you're in the same boat as everyone else, there's no relative loss, and most importantly you don't stick out as someone who did something as risky as to go against the prevailing, albeit pretty clearly nonsensical, sentiment.

So basically, game theory tells you pretty quickly to just go with the thing that makes no sense if you're optimising for some (weighted) cross of what's best for the organisation and yourself as the decision maker.

I was just thinking how it'd be great if there were newer, modern things like this that had sprung up in response to newer technologies.

I guess it's one downside of dematerialisation with digital tech - I can't think of a single thing that would make sense. Everyone's got their own virtual portal to all the new technologies that come out, there's not much to look at out in the world.

Maybe as more progress happens in physical 'world of atoms' type things we'll see a bit of this come back.

I think weirdly, ads embedded in AI search responses actually maybe do have a chance at being helpful (as long as it's clear from the context of the question that I may be willing to pay for a solution) just because they could potentially be quite well matched to the specific thing I want, or if they're not quite as well matched but offer other benefits, explain the difference.

At the moment search ads aren't very helpful because you have neither of those things. You always get them for any type of query, and when you do get them you don't know if the thing being shown will exactly solve your problem, or only approximately, and the work is much more on you to find that out by reading the product's marketing pages further.

If all that could be done for you up front, reasonably honestly, then I could see it being useful. I mean to be sure, in some small percentage of searches I really am looking to buy something and really do want to be usefully, honestly pitched on available options.

is the point of doing it for the artistic value / challenge or are there other benefits of not using a mesh or physical model of the object?

interesting thing about the scoring effect narrowing the types of writing that generate the higher average ratings.

I guess also there's something fundamental about next token prediction that is going to narrow in on 'stable' ratings. Let's say for the 4/5 rating you have a wide range of styles, there's also this question of then the style of 4/5 isn't going to be cohesive, so which one do you pick?

Any output that mixes them up is going to get rated lower in later testing, and then if you have somehow to pick one, you've got to stick with it, which seems like it would be complicated to put into next word prediction weights. You'd need a different branch of weights for each style or something.

So not only does the rating process itself push towards a generic style, but the model 'prefers' training on this generic style, i.e. gets to better-seeming results faster.

it's almost certainly not true yet but at some point there might be an equilibrium reached of speed Vs quality (and let's not forget, cost) where it's true for most of what you do.

Perhaps you'd still turn to hosted models for the hardest tasks, but most tasks go local. It does seem like that would make demand go down significantly.

Of course that's all predicated on model advances plateauing, or at least getting increasingly more expensive for incremental improvements, such that local open source models can catch up on that speed/quality/cost curve. But there is a fair amount of evidence that's happening. The models are still getting noticably better, but relative improvement does seem to be slowing, and cost is seemingly only going up.

I think this instinct is intrinsic, and comes from really caring about detail and wanting to fully understand it and own it.

That's what drives it, and I don't really think the extrinsic things about the way you learned (while helpful) have that much bearing on it. It comes from you and you should take credit for it.

I think if you were learning today you'd probably find have the same feeling and do just fine because of it.

> Especially with the advent of AI, it feels like the time I had left to learn and actually build something has run out.

No, this is wrong.

Get your head down. Learn fundamentals. Practice and develop real skills. Ignore anyone saying this is irrelevant now. Let them talk, keep learning and building stuff, while using the new tools.

Give it a few years and you'll find the narrative has changed again, meanwhile you've got a few more years of experience under your belt. Avoid the noise and just focus on building.

I think a tell that many of these deals likely aren't real and are basically just PR is the numbers are super round and digestable.

That's a clear signal that little analysis has gone into the numbers and, most generously, there's nothing but the shape of a deal the details of which will be ironed out and adjusted in practice.

I get that the amounts of funding and capital being sat on for the respective parties are collossal and lead to rounding that doesn't make sense from the point of view of an individual any more (what's a few million at this scale, just round up to nearest 10, etc) but deal sizes of literally round numbers of 100s start to stretch credibility on whether any real analysis was involved.

In fact it'd be a ridiculous coincidence if it had been. They're the kind of figures where you'd recheck your calculations to check it's right as it seems too perfectly round.

a bit of an aside but what's amazing is that Docker's recent beta VM for Mac (I think released a couple of months ago now) has dramatically improved the performance you get out of your CPU.

Using a macbook air, even a recent one, before this Docker was definitely usable but noticably slower. Probably still worth it but a noticable tradeoff using it as a dev machine Vs a pro. Now that tradeoff has basically gone away.

> Natural selection will take care of them in due course

Wonderful articulation. There's a plethora of prognostication about how AI will change everything in software and beyond and the thing I keep thinking is, well, when will the talk stop and the demonstration of results commence. It doesn't seem to have as yet.

If it works, it'll work. The methods will spread and quickly be accessible to everyone, and progress will go on. That's great.

If it doesn't work, we'll also see that in the absence of real results. And simply stating you are seeing it doesn't qualify. It must be something we can all see and use that is unavoidably, undeniably real.

I just set this up for npm, here's the command that worked for me:

npm config set min-release-age 7

The '7' is days. This is the only format that worked for me, just a single integer number of days.

Confirmed by trying to install the latest version of React 19.2.6 (published 5 days ago as of the time of this comment). It failed with a comment confirming that it could not find such a version published before a week ago.

There's a lot of truth in what you say but I think the conclusion you landed on is too broad.

There will exist people moving quickly who have failed to plan, but a lot also incorporate moving quickly as part of their plan, simply because that's how they prefer doing things.

It's true that this kind of planning is vulnerable to unexpected problems - a missed connection, a queue, whatever it might be - but over time it can still work out rational if you accept this risk and just want to spend less of your time in aggregate in transit, with spells of over-provisioned waiting time, or just prefer the experience of moving quickly (there is much said about the benefits of slowing down, less said about the equally valid disposition of finding flow in the act of moving quickly, which many people also experience).

this is so true and I think it's very instructive to have a regular look through this lens when thinking about building something.

You've got to think and care deeply about what you're creating while at the same time understanding it's of approximately zero interest to those who you're building for outside certain key moments of interaction. Try to just nail those as much as possible and beyond that, get out of the way.

I think this is the core of good design, that things make sense, are nice, and well explained to the point they are even fun to discover and explore when you care to go looking for them. If you don't care to, they're invisible and out of your way.

appreciate the response. I understand better now, and agree with a lot of what you've said about kinda the mechanics of scripting stuff 'by hand' being just quite fun and satisfying but maybe no longer the expected way to do things, and so in some sense the sweet spot of that being something you can be paid to do is largely over. Interesting times for our profession.

I completely understand the active/passive difference but I have a question for you that I think especially applies to sysadmin: isn't the knowledge you have and your continual learning just as important if what you're essentially doing now is using an LLM to help you find problems, propose solutions, and test the solutions?

Maybe it's even more important since you've gone from crafting your own solutions to reviewing the viablity of solutions from the LLM which occasionally are going to introduce new ideas, do things in a similar but slightly different way to how you would, or even be subtly wrong in ways that also exercise your ability to adapt and learn and nudge it in the right direction instead.

I don't really understand how the alternative could be true, in the sense of your knowledge not being relevant, as that would imply a couple of things that don't seem true as of now: that LLMs always produce optimal solutions in any given scenario, and (as a corollary) that sysadmin is entirely automated apart from some sort of thin beurocratic human approval/deployment layer.

In my experience so far I've found sysadmin type stuff to actually be what LLMs help me the least with, excluding text-in-text-out scripts, precisely because the setup often has to be so custom to the system, there's loads of side effects that are hard to communicate to the LLM so it oversimplifies and gets things wrong often.

So hopefully you can understand the implied challenge behind the question. I'm not saying your feeling of it being less fun is invalid. But I'm really curious about what you said specifically about the fun of applying knowledge and learning having been diminished. What do I have wrong?

In my experience the majority consensus is to maintain a quiet, generally polite environment on trains and buses.

But that's precisely the problem, it only takes a very tiny minority to change this. If one group, one person sometimes, in a carriage of 50 people decides to go against this, then that's that. It's not even particularly common, but it happens, it's random, and so it's just something that must be contended with.

I appreciate what you're saying and am a big fan of long distance train and bus journeys myself and have done a lot of both, sleeping and not.

But one huge factor that you have to contend with is the randomness of the tragedy of the commons problem on public transport / shared transport. A train journey can be blissful to sleep on right until a loud group gets on and sits across from you and there's no seats available to move.

I think this is something that can't be overlooked, especially if you're talking about something like a short trip where if you don't sleep well en route, quite a large proportion of the trip time is going to be affected. Having a private vehicle where you can guarantee control of your environment is a really huge plus.

Did you consider IntelliJ, even just the community edition?

If not you really should. IntelliJ with Java is one of the best dev experiences I've ever had. I'm a VSCode fan for most other things but for Java I wouldn't even remotely consider using it over IntelliJ if I had the option :-)

My guess would be this is less driven by product philosophy, more driven by trying to maximise chances of a return on a very large amount of funding in an incredibly tough market up against formidable, absurdly well-funded competitors.

It's a very tough spot they're in. They have a great product in the code-first philosophy, but it may turn out it's too small a market where the margins will just be competed away to zero by open source, leaving only opportunity for the first-party model companies essentially.

They've obviously had a go at being a first-party model company to address this, but that didn't work.

I think the next best chance they see is going in the vibe-first direction and trying to claim a segment of that market, which they're obviously betting could be significantly bigger. It's faster changing and (a bit) newer and so the scope of opportunity is more unknown. There's maybe more chances to carve out success there, though honestly I think the likeliest outcome is it just ends up the same way.

Since the beginning people have been saying that Cursor only had a certain window of time to capitalise on. While everyone was scrambling to figure out how to build tools to take advantage of AI in coding, they were one of the fastest and best and made a superb product that has been hugely influential. But this might be what it looks like to see that window starting to close for them.

With respect I'm not sure what you're saying follows as a challenge to what I've said. Perhaps because I didn't phrase clearly enough.

I don't think that. In fact I spent years at a company whose product let people build software backed by spreadsheets so I'm at least a little acquainted with that corner of the world :-)

The thing I'm saying is that among those who want to engage in building software via coding, I don't accept that caring about coding craft and caring about building great products that solve problems for people are opposing points on a spectrum.

If anything I'd argue the opposite, that these qualities are correlated. Again, speaking about people who are interested in building software with code.

I think the thing of building useful software with software (like spreadsheets / AI builders) while deliberately not wanting to engage with coding is a discussion apart from this. There's apparent overlap because it's true to say that those people are concerned with building useful things and not necessarily concerned with coding. But the fact they're not concerned with coding by definition puts them out the scope of the first conversation, it's just a different thing.

I keep seeing this idea repeated, but I don't accept the dichotomy between those who care about 'crafting code' and those who care about 'building products' as though they are opposite points on a spectrum.

To me, the entire point of crafting good code is building a product with care in the detail. They're inseparable.

I don't think I've ever in my life met someone who cared a lot about code and technology who didn't also care immensely about detail, and design, and craft in what they were building. The two are different expressions of the same quality in a person, from what I've seen.

> if you don't already know what it means or how you should read or say it

Google I'll grant you, though it's still pretty phonetic and easy to read. The other two not at all, they're incredibly well known instantaneously recognisable words.

Interesting, thanks for the context! Makes it more understandable as a choice.

everyone has a first time they see a thing and don't yet know what it is.

Using a brand as a filter where you have to already know what it means to get it is exactly the opposite of what it's supposed to achieve.

Consider the most exclusive (successful) brands that exist. Even there, where exclusivity is a brand goal, none of them have this property of being obscure on first contact.

It's an opinion, and you feeling no particular way about it is equally valid.

But I did justify and maybe to reword slightly, surely if one of the main drivers is opening up research, the brand name should be something that's less obscure and more accessible / understandable as to what it is on first sight?

Maybe arXiv evoking the word 'archive' with an ancient Greek twist does that for some, but it's clearly a bit cryptic for many, and if the point is to open up probably the brand should just be something much plainer.

Very unrelated to the article, but I think 'arXiv' as a brand is bad, and really detrimental to what the institution aims to accomplish.

That is, it's not readily parseable, it really gives an insider term vibe - like this isn't for you if you don't already know what it means or how you should read or say it. It sort of reminds me of the overuse of latin and latinate terms generally in the old professions and, well, the academy.

Just always struck me as being somewhat at odds with the goal.