A shame that Pangram flags this as AI.

https://www.pangram.com/history/c0a9cde2-7a5c-4588-83a3-0269...

The issue with this is that we don't know how it works. Generally speaking, we know how the level of abstraction that we were born with works. We might have some understanding of one or two previous levels, but that decreases the farther down you go. We might understand the next level, and some of the next after that, but eventually people will be making things that we don't have the context to understand without having to unlearn a lot of what we know now.

I'm old enough to see this process in action; I used to be young and in possession of esoteric knowledge that made me infinitely in demand and now most of the things that young people have esoteric knowledge about is things that I don't particularly care about, and I'm left with a lot of finely honed skills to solve problems that have mostly been abstracted away.

It is no small feat to put in words that we are losing something almost as quickly as we are gaining something. The undertone, despite leaning into nostalgia boils down to losing control and this uneasiness I feel growing daily. It is already shocking to a certain degree seeing very young people not being able to use a computer in the narrow sense because all they ever learned was touch interfaces and apps. Curated content, curated interfaces - everything that resembles some kind of hardship ironed out in thousand steps of iterations to appease the market which means the lowest common denominator.

But I also see that the people who can create the absolute most and the good things and the working things and the maintainable things nowadays are the people that have gained a tool, but not lost the knowledge of the medium we are using it on because we are tied to this old world so perfectly put under the spotlight in this blog post.

There was a sweet spot with computer technologies for some decades where hobbyists could afford to experiment and even push the envelope in the nascent field of computing - similar to genetic radiation, many niches were formed and rapidly filled. The computing biome has evolved to the point where most entities are not operating at the low-level abstractions that were once the only means of interacting with the computing environment, instead they operate now at the highest levels of abstraction we are capable, so called "natural language".

"The difficulty was the knowledge. You came to know that machine the way you come to know anything that pushes back. The resistance was the whole medium. You only ever know the things that you can lose to."

We who grew up in this era formed a hands-on engineer's knowledge of these systems, built from experience and practice, learning these layers of abstraction as the bleeding edge developed. Many these days have entered into a world where there are easy answers abound, they just might not be right, and one has to gauge how much they care about correctness.

I'm one of the greybeards who has the 2400 BAUD modem negotiation tone sequences emblazened in my neurons.

For a while I've been meaning to set up some Wireguard connections among some of my systems. Being as busy as I am with work and family, I've relinquished that to Tailscale for now.

Sure, I could have sat down and jumped through the hoops to get everything set up and working across my various hosts, including network routes, firewall rules, key pairs, systemd units, and so forth. But the "cheap and easy" alternative was right there and worked (except when it forces re-authentication).

With LLM agents, I was able to effortlessly analyze my existing network and produce tailored scripts to do precisely what I wanted. All I had to do was review the scripts for potential security issues and what not. Looking at the script, there are 3 or 4 specific tweaks that needed to be made to my network routing rules given my network topology. I could have read a few man pages and iterated on the script by hand to eventually get there after maybe an hour or two of futzing.

The availability and effectiveness of the agents is simply too tempting for me. I'm not sure what this means about my skillset, or if that even matters any more. I am fairly confident that, so long as my brain still works well enough, I'll always be able to RTFM and figure things like this out myself. At this rate I wonder whether my kids will have the same ability. And I also wonder how much that will matter.

Regardless, I'm still helping them figure things out the "old way" without over-reliance on LLMs. One thing I'm fairly certain about is that failure to develop problem-solving skills can only put them in a worse position in life, no matter how capable AI becomes.

> You opened files like autoexec.bat and you read them. Sometimes you built a boot disk for a single game. A floppy whose entire reason to exist was to start the computer in the configuration that one program demanded.

Is the premise here correct? I'm not sure that I'm convinced that a 1990s computer user who knew how to edit autoexec.bat or insert a floppy to boot their computer "knew how it worked" in a meaningful sense.

The stack of abstractions is deeper now, and all indications suggest it's not going to stop deepening. But I think the abstractions were already quite deep by the 1990s.

(I think the classic error here is a demographic one: computer nerds always poke through abstractions, because they do it for fun. I don't think that's going to stop, anymore than web browsers stopped people from writing kernels. If anything, we write more low-level code than ever, because access to the prerequisite knowledge is less gatekept than before.)

“The knowledge is not in danger, in fact, it has never been safer. The AI models have read every manual that no human reads.”

I disagree. If you ask a model for a manual and it regurgitates that manual from its training data, it’s over-fitted. It will regurgitate something that looks like a training manual. Or whatever fits your query about training manuals.

You still have to push back on them sometimes when you spot an error. And you can only spot them if you already know what you’re looking for and should expect. Otherwise you have to ignore the output and just get the links which… could be outdated or made up as well. You’ll never know until you verify the results.

And this degrades with compression and time.

There’s no royal road. I agree that trying and getting frustrated and having to take the effort to understand something pays off in spades. I just think it’s still worth it and vastly under appreciated in this era of “everything fast, now.”

@ryancbriggs - 18 Oct 2024

> When I was young I fixed my parents’ computer and now that I’m older I fix computers for my kids. Are we the only generation that knows how computers work?

https://x.com/ryancbriggs/status/1847391612428517844

https://xcancel.com/ryancbriggs/status/1847391612428517844

I resonate with every example given - setting jumpers by hand, sound card interrupts, autoexec.bat. I'm also a happy user of LLMs and agents. This article captured for me what is lost - which, as others point out, has long since been lost, if ever had, in other fields (e.g. modern cars vs. the Model T). I wouldn't go back, but I can still have a sense of loss.

Beautiful writing.

Modding communities are still going. Kids, afaik, are still playing around with hosting minecraft servers or whatever is en vogue/cool/meta/etc nowadays. DIY 8-bit computers are gaining popularity.

IMO the fact that something's become very mainstream doesn't necessarily mean it's been watered down for everybody. There will always be people with various levels of curiosity and enthusiasm.

I doubt you ever understood the solid state physics, semiconductor fabrication processes, supply chain logistics, monetary policy, shipping routes, mining engineering, etc. "Knowing how things work" is a stone-age attitude.

At this point, I sound like a brand ambassador. But I highly recommend The Machine Stops by E.M. Forster. It's a story about what happens when the machine of modern life that we all rely on suddenly stops. It's been operational for hundreds of years, and there is no one left who knows how to fix it.

> The graybeards are aging out, nobody compiles their kernel anymore, and someday something deep will break and there will be no one left who can climb down and fix it. Maybe. But I think competence is the part that’s fine.

> knew a beige computer in 1995 that wouldn’t run a game until I had rearranged its bits by hand. More dependent than ever

If you look at previous article from this author, it says how Mac is amazing and how Linux sucks. Kids like that in 1990ties would buy expensive consoles, and would not deal with hack PC's to get free games.

Many people today are still dealing with cheap shitty hardware, 7 years old Android phones and sketchy ROMs... Just because there is no other option!

https://unix.foo/posts/it-will-never-be-the-year-of-the-linu...

I came into the US tech industry in 2011 from a CS program (programming on my own longer), which was basically a pipeline into Java or web dev at that time (the classes on other things like OS, compilers, and FPGA were a thing, but seen by most as a hurdle not a promising or practical career pathways).

Most of the people I dealt with for the decade following that (i.e. pre-LLM) had little clue how any part of computers worked, and I don't intend that to be particularly pejorative, it's just that it's been somewhat easy to carve out a niche doing something to do with programming while having little understanding of the small or big picture.. all heuristics and applying working patterns.. for a few decades.

You can still understand whatever you want, today, with added tools. It's just a choice to turn your brain on or off. I think LLMs are perfectly fine as a learning tool to interrogate a subject, do comparatives, and then formalize your understanding by reading the sources. At a macro level brain rot is real, but it cuts across all generations and it started long before LLMs.

>The knowledge is not in danger, in fact, it has never been safer. The AI models have read every manual that no human reads. They will recite, flawlessly and forever, exactly how all machines work. If this were only about competence, it would be the most secure moment in the history of computing.

Obviously this person doesn't have enough experience with the current crop of AIs. This is the exact reason why we should be concerned in the first place. Someone has to design and build the next version of everything, and AI isn't qualified to do the job, and might never be.

>What is dying is acquaintance. The plain, unglamorous intimacy of having fought a particular machine, and lost, and gone back, and finally felt the thing give.

This is true. But then again, who among us had to get up in the middle of the night, and trudge out to an outhouse? Who had to shovel a bit more coal into the furnace? Who had to pump water, and heat it on the stove? Who had to split wood, and stack it for the winter?

There are many, many things we're no longer acquainted with, and that's sad, but still ok. What's not ok is losing the competence required to maintaining the infrastructure and supply chain supporting society and civilization.

This might just be a personality trait of me, but I really like technology that's transparent enough that I can fix/modify/understand it. Opaque technology gives me an ick. It's not really a complexity thing -- Linux has this property of being transparent even though it's extremely complex. The way he describes old computers.. man, I loved that about them, there was nothing _secret_ going on, you weren't worried about telemetry or weird background processes. Then again, I still drive a manual transmission internal combustion car in 2026, so maybe I don't represent the world.

Then again, maybe there's light at the end of the tunnel. Even though AI boosters kind of annoy me, I do appreciate that they're tinkering and hacking and working to understand the technology on some level. I think there's always going to be some small number of people that are like this, in the same way there are still people that look at disassembly and understand CPU caches.

I wanted things to be a little easier, but not this easy

Two thoughts:

1: This is why I prefer console games. I just want to have fun without fighting with the machine.

2: There are plenty of people who appreciate old techniques and methods; and keep them alive. Think of going to a museum and seeing someone demonstrate an old craft or reenact how a craftsman did their job. For example, in my town there is an old, water-powered corn mill that still runs and sells corn meal.

I worry less about whether people know how it all works.

I worry more about whether people care and consider it a problem when nobody knows.

>To play a computer game in in the 1990s, you first had to understand how the computer worked.

As someone who played plenty of computer games as a teen in the 90s I assure you that I did not know how it worked. I learned how it worked later when I got a CS degree at university. Following the instructions from the booklet that came with the game may have helped me to get it working, but there was minimal understanding.

Speak for yourself but I certainly don't know how it works.

Also, if you don't think the difficulty is the knowledge, I'm sorry but I must disagree. There has been more than one government or corporation or large institution that has tried to destroy history and knowledge in the past.

I think it's fair to say that knowledge is also at risk.

>What is dying is acquaintance. The plain, unglamorous intimacy of having fought a particular machine, and lost, and gone back, and finally felt the thing give.

I think this is a universal feeling that accompanies any technological innovation. My phrasing is that new technology unbundles the thing people want from the craft that was formerly required to get it; any craft requires someone to learn and achieve through struggle.

Yes, it was not easy to install and play a game on the computer in the 90's. Today, we also don't want to wait for the game to boot.

This is sort of the story of the telephone system of the 1950s-1970s, or electricity in the early 1900s, or cars from 1950-1980s, or airplanes from 1910-1939.

I have no idea how an electrical transformer works (well, other than the bare theory I learned in physics courses), or how power gets from the power company to my house, or how the circuits in my home are setup. I plug something in, and it works, and occasionally I throw a breaker if something is malfunctioning. There's no resistance there (pun not intended), and there shouldn't be. People got killed trying to wire their own homes.

I used to read about phone phreaks from the 1970s that could do black magic to get free long-distance phone calls. When I grew up in the 80s, that was basically gone. You picked up the phone, got a dial-tone, and called. And now it's really gone, with everyone having an encrypted cell phone connection over 5G, and your IMEI and IMSI being phoned home to every tower you connect to.

It's the nature of technology and capitalism. As the technology matures, it gets hidden away to become increasingly invisible to the end user, so you just do what you want to do with it. And then the engineering resources get spent on new problems.

I can't help but think this type of step function change has happened with computers before.

The change from punch cards to magnetic storage certainly made it so you didn't have to "know how it works" for every single bit.

The change from machine code to a language like Fortran brought about such an abstraction that a Fortran dev didn't "know how it works" at that same level anymore.

At this point, the layers of abstractions between using a React component and something being rendered is immense. React VDOM, the real DOM, browser render engine (which sits on abstractions like ANGLE, skia, etc), calls OS APIs, which call driver APIs, and the lowest level of anything it is still C/C++ that is compiled (abstracted) to something closer to what the hardware expects.

I won't bore you with the ChatGPT output details, but it estimated at least 35 meaningful layers of abstraction between a React component and being rendered to the screen. LLMs seem to be the latest level of abstraction to make it so we "know how it works" less than before.

With how seriously rise of LLMs damages schools and university education, and thus next generation of comp sci graduates, at least we can hope to secure our arcane knowledge jobs for long.

> The machine was made of edges and you cut yourself on them, and that is how you found out where they were

> ...having fought a particular machine, and lost, and gone back, and finally felt the thing give

mayhaps this is because our computing paradigms are stuck in the 70's

I'm still nostalgic for the times when I had to enter the bootloader using the keys on front panel of the PDP-11 to then loaded the OS from paper tape. (not to mention multi pass compilers using paper tape between the phases...)

This is also a fear I have, I am answering it with building bigger things with AI: what I loose in expertise in the details, I gain in the pleasure of architecturing bigger things.

I wouldn't calling it learning more and more like "cycling through SoundBlaster DMA and IRQ options until the sound work". Still, there was an intrinsic curiosity that isn't as prevalent.

Why do you have to know how the whole thing works?

You can know how your entire farm’s water system works. But a city?

Somewhere in between those extremes, you just have to let go.

> They will have a tool that does everything and asks for nothing, and they will be as easy with it as you are with the light switch you never once thought about.

Oh come on! Of course I wondered how a light switch work, and I then learnt. I remember taking apart broken electronics as a kid, and that later morphed into also trying to repair things. Including the computer (both hardware and software wise). I remember ending up reinstalling the OS so many times as a kid on the computer I had access to when I broke it in various ways past what I was able to fix.

Sure, not everyone will have that drive to understand how the world around them works under the hood. But for engineers and scientists I would expect a far higher percentage to have that sort of personality.

It doesn't matter if it isn't "pushing back", just that I don't understand it is enough to catch my interest and a reason to go poking at the thing.

The graybeards are aging out, nobody compiles their kernel anymore, and someday something deep will break and there will be no one left who can climb down and fix it.

I dunno. I suspect it'll be slightly different in the OSS world[1]. There will be some folks who can climb down there and fix it, but since that skill is no longer valued (as in, being able to do that isn't valued by most users now, much less in some hypothetical future). And they will be expected to do that, now, without thanks. And when they say "I'm too old for this shit...you can go pound sand" because this was one unpaid insult too many, users will shrug their shoulders and load windows or buy a mac because those companies are paying & tasking people to keep things running. And by inches oss ceases to be a thing.

[1] Yes, I know there are many oss devs who get paid for their work. Many critical contributors do not.

We always were the only people who ever knew how it worked. In 1990 people fellow students called me to fix their computer, they had absolutely no idea how any of this worked. No. Idea. Yes, the machine was being difficult; but their reaction wasn't to fight it, or understand it. It was to call someone to do it in their stead.

I'm not sure things are very different now.

Gee, I sure hope pump 6 never fails.

Some of the best systems programmers are under 20 years old what do you mean

Folks who keep mentioning that this is no different than any previous upward leap of abstraction in human history are missing a key point that the frontier labs are certainly not missing: this is the first time in computing that you are becoming completely dependent on a _subscription service_. I don't need to know how my CPU works because it continues to work once built. Once I outsource all cognition to a billable service, I am forever and continuously in thrall to someone else's revenue strategy.

https://en.wikipedia.org/wiki/When_the_Bough_Breaks_(Star_Tr...

Moral panic. We all have private tutors on every subject at our disposal now. It takes some special kind of mental gymnastics to conclude from this that no one will learn anything anymore henceforth. The article is just a long-winded way of saying "Kids today have it too easy", or, equivalently, "I'm getting old".

"To play a computer game in in the 1990s, you first had to understand how the computer worked.

So you learned. You opened files like autoexec.bat and you read them."

Ehh I dunno about that. I rarely, if ever, had to mess with any of that junk after Windows 3... I also didn't have to deal with any IRQ issues. So seems like it was already mostly abstracted in the "1990s" lol

I may not be a "typical" engineer as much anymore, in that I don't seem to be excited by knowing the intricate details of how things work as much as I enjoy knowing the capabilities of the systems that enable the projects I work on, and working at a higher level that might be more abstract and conceptual. AI enables that very well in that it enables jumping between paradigms and enabling creativity by removing a lot of the grind that was necessary in gathering technical details. I find it less appealing now to get into the weeds of how a thing works, even though at 10 I very much did. Like the author, I dug into the details of exactly which bits needed to be activated to make a particular program work. But as I aged, I was drawn to higher levels of abstraction, I think because I realized I could do more overall by piecing together bigger blocks. Yet I know colleagues who like to be involved in a very granular level of detail. I have many friends who almost revel in their knowledge that they are the ones who know precisely why something works the way it does. I think about the story of the NASA engineer on the Apollo 11 program who understood the assembly so well that he could confidently answer on the spot the moment the radar overload "1201 alarm" error flashed that the mission was still good to go. Some folks get so deep in this perspective that it almost seems like an affront to suggest they may be wrong about one of those details. And well they should, because precise people are very much needed to understand intricate systems. But it makes me wonder how they feel with AI being an indeterminate system - one where you can never really know what the answer will be every time. Likely still correct, and getting better every day, but also possibly different every time. Added to that, it's exponential spread across the software engineering domain. For me, even as someone who likes high-level systems, I still relate to the feeling that the detailed part of me that still likes some of the internals may be less focused on in the future. Even for me that's kind of sad. But I am also curious about my colleagues who are super detail oriented - how do you feel about AI and how it changes the focus on that detail aspect?

When I was young I was so naïve. The whole world seemed to be barreling straight towards the things I liked and was interested in. Every year there were more and more nerds, more people with computers, more people playing video games. It felt so much like I was the future, that in a couple of decades everyone would be chit-chatting about what was coming, buying and comparing devices, etc. I could not have conceived that people younger than me would have less computer knowledge than me. If at twenty you had told me that I would wake up one day and teenagers no longer knew what a file extension is I would've asked you who won World War 3.

I've been thinking that there might not be new programming languages. The amount of code in the current popular ones will explode, so that's what all LLMs will be trained on.

Good luck coming up with a new language and getting enough content out there that LLMs will be fluent with it.

If true, I think that's a shame. There's plenty of innovation still to be done.

This has always been true. I never fixed my car. I knew how it worked well enough to know, hey, that sounds like its coming from the exhaust pipe. Then I took it to the mechanic. I can do basic maintenance on my bike, but I still take it to the bike shop. I have a small collection of vintage cameras, which means tracking down the few people left who know how some particular model works, might have parts. If your Synchro-Compur shutter needs parts, forget it. For most people, most of the time, the assumption has always been that someone else knows how to do that.

It doesn’t have to be this way, but the cost is performance (and falling behind competitors).

> The knowledge is not in danger, in fact, it has never been safer. The AI models have read every manual that no human reads. They will recite, flawlessly and forever, exactly how all machines work.

That's wrong, and that's exactly why the loss of knowledge is such a problem. LLMs do not, and cannot, actually know a single thing. They are a statistical model, not knowledge. When they give out wrong information (and they always will, by their very nature), you need someone with actual knowledge to be able to recognize the BS and correct it. But we are losing the knowledge, and unless things change we will be no better off than the people in dystopian sci-fi stories who pray to the machine god because nobody knows how it actually works.

Try getting a Linux laptop to just go to fucking sleep and not drain it's battery flat within a few hours, and wake up without losing wifi.

There are more important battles for humanity to fight than someone trying to figure out how to configure Linux correctly for their hardware. I won't miss the need to waste time fighting the computer going away.

Paging Vernor Vinge to the white courtesy phone.

I recently had a run-in with security restrictions at work that only blocked the abstraction layer at the top, and were utterly surprised to discover that if you go down one level none of their restrictions did anything.

They eventually decided to keep their head in the sand and pretend like their restriction was useful.

The issue was a complete lack of knowledge of how the system actually worked one layer down.

Who cares?

There have always been layers of abstraction. I've been around for a while, and when I was a kid, the two choices I remember seeing were assembly code and simple semantic languages like BASIC.

Assembly seemed like too cryptic for me to really even follow and I never really did learn it, but at the time I remember people would say that assembly was easy and basically plain English compared to machine code.

As recently as fifteen or twenty years ago, I would occasionally check in and think of how unbelievably far away we had gotten from how the computer actually works. Like, you can just write "open window" and a window opens. Amazing.

Of course, those people writing machine code didn't need to really understand what P and N were in a transistor, let alone how an integrated circuit pulls it all together. And I'm not sure how much those guys knew about silicon dioxide.

The more complex things get and the more layers of abstraction there are, the more impossible it gets to really master things all the way down to first principles.

So what? People can carve out whatever chunk of the stack they want to really understand if they want to focus their lives on it. And for everyone else who's just trying to accomplish some other goal with computers as the tool, they will naturally use the highest level of abstraction and the simplest one for them to use, which is exactly what they should do.

Just wait until they shred all the old useless books

Does anyone have a list of all the times this sentiment has been incorrect over the decades?

There's no arguing down that we have a greater amount of information about old hardware and software easily available now compared to back then, and there are many more enthusiasts as well.

This kind of cognitive dissonance has been going on in other disciplines, like music, since their inception. Guess what? There's thousands of highly talented young people on social media covering it all.

What people are actually upset about is that there isn't new "old stuff" and they can't make money off what can now be thoroughly understood by anyone.

Don't get me wrong, AI is a total shitshow and we're entering another winter, but there's also no reason to be jealous of what is making money right now.

Competence Does Not Mean What You Think it Means.

Please don't fucking tell people that AI is competent. It is not and it cannot ever be because it is not alive.

People nerd sniping the op add nothing of value to the discussion. Take a break from HN if you’re just going to shitpost.

This and it was demonstrated in Star Trek The Next Generation: Season 1 Episode 17 "When The Bough Breaks" [1]. They did not know how to fix their computer system or even where it resided. It did everything for them but was also killing them and making them sterile. There was nobody left to figure this out until the Enterprise crew happened along. This could happen on Earth. Who will save us?

[1] - https://www.youtube.com/watch?v=5WWyKQThSKg

>The difficulty was the knowledge.

Please write your blog posts yourself. I don't want to have to parse through this stupid claude output to get to your point. Literally just posting the prompt would be better than this.