This has not been true in my experience. The bar of what is possible has been moved dramatically. So my daily quest is not to continue to achieve our old objectives, but rethink worthy objectives for our new tools.
The blasé attitude with which people talk about “moving up the stack” as if it’s a foregone conclusion that it’s the right thing to do or even an accurate description of what’s happening is easily one of the most disheartening aspects of this whole movement.
The article is not about the output but on the process. Sure you can produce more and more quickly with AI, but at the price of losing the ability to do the same without it. And that's been true in my experience
The average human is no longer able to hunt animals for food anymore either. I think it's just the domestication of humankind as it has been ongoing for thousands of years
> The average human is no longer able to hunt animals for food anymore either.
The average human may no longer desire or have a need to hunt animals for food. But re-introduce that need and they will do fine. Kids and adults continue to be able to pick up fishing for the first time as well as handling a .30-30 or 20-gauge.
Using my brain to solve abstract problems and getting money that I can exchange for food, in the comfort of an office or a home, is already way past hunter-gatherer. Now if I don't even get to use my brain that's more a dumbification than domestication.
10 minutes of AI doesn’t ruin someone from programming or solving fractions either, it just lowers the ability short term. Likely not by making someone dumber but instead impacting motivation. Give someone a calculator and then take it away and you would get a similar result
Unfortunately there is no way for us to try this. “yes” might very well be the answer. My hunch is that although it would seem pointless, you would still be able to go through the motions since the work is largely physical. For knowledge work, concentration and perseverance is half the work itself.
> The average human is no longer able to hunt animals for food anymore either.
And that is not a good thing. We shouldn’t celebrate or ignore the loss of basic living skills, especially when what we get in return is a nightmare scape of a society whose whole purpose is to dominate your thoughts and fill you with anxiety to suck you dry.
"Basic living skills" are relative to the environment and change by culture, location, access to technology and so on. In our environment, we don't need to hunt. It has been fully superseded by supermarkets, and that can reasonably be expected to continue into the future. That's literally the only reality we have ever known, and the only reality towards which adapting is worthwhile.
The new hunting-equivalent basic living skill would be the ability to go to a store, orient yourself, pick reasonably priced items, ideally choose healthy ones and avoid the temptations of junk food, check quality and macros (calories, protein etc)...
I think I get your point. I think what you're getting at is that hunting etc is a fundamental skill, below this abstraction we have built, and if you would be dropped into a forest and left to your devices, you'd still be able to handle yourself. But I just think that it's an interesting mental exercise, but nothing more. I really don't see it as a tragedy.
Tl;Dr "Basic skills" are relative. Hunting is now an outdated, impractical, unusable skill to hone, and a vastly inferior source of food.
If anything, I would claim the opposite ( and agree with you )
Not only has AI allowed me to start projects without knowing all the steps ahead of time, it has helped me proceed through each of those steps to completion.
"For the first experiment with 354 participants, one group was tasked with solving 15 basic fraction problems without help, while another had ChatGPT open on the side to use for assistance and to even ask for the answer. The group with AI access started off more accurate than the group without it. Then, after 12 problems, researchers took away the AI tool. Almost immediately, the people in that group stopped solving questions accurately."
Looking at the design of the experiment, it seems everyones brain was primed to think "I have AI at my disposal" ... and then had the framework shattered when it was taken away, which could have affected the test.
Perhaps this study exposes "conversational mindset" versus "mathematical mindset" switching times ?
Theres only one thing I'm certain of ... Claude loves me. :D
At which level of instruction abstraction would you deem it to be someone's creation?
You could argue anything high level is not someone's creation (e.g, the use of other people's libraries, compiler, machine language etc.)
You are not just going up an abstraction. Whether you are using Python, C, Assembly, you are still engineering because you are writing the specific instructions that make the software work. In this case, you are more like a manager than an engineer that is managing something to engineer for you.
Calling scipy.spatial.Delaunay feels about the same level of abstraction as telling an LLM "write me a routine to calculate Delauny triangulation", except the LLM can do it in any language, and I can trivially tweak the algorithm if I need to. If anything, using LLMs to generate code feels like going down a level, because I can now be bothered implementing things from scratch where previously I would simply have used a library.
You can't convince me that shepherding an LLM to re-implement a library function involves less "engineering" than just... calling the function.
I consider it at the point I didn't build it with my hands. If I'm placing the girders, I built the building. If I'm instructing someone to place the girders, I didn't. In that case, the best I can get is "we" built the building.
A more apt comparison would be the producer role (not the executive type, I mean the Project Manager type of roles). And to be honest, I've seen some amazing music A&R being the reason an album is a masterpiece without ever pushing a button or playing an instrument. But none of them would call themselves musicians.
Or is it more like creating machine code but using a tool called a compiler? If you've ever made anything with AI you know it by default generates things that aren't ideal. You still have to go in and debug, make the UI better, think of more elegant ways to present things. The fact that you're focused on those issues instead of tediously finding the block of code and maybe tediously looking up ways to fix / make it better is probably an overall good thing in the long run. We've lost the ability to code in assembly I'm not sure that's made software or life worse even if coders as a group are in all likelihood less intelligent these days.
In your analogy maybe it's more like creating a pizza except you didn't have to make the cheese, grind up the flour, go find the water in a stream somewhere, grow the tomatoes yourself, butcher the animal for the meat, etc.
You can throw away the compiler and the developer who created the software will still understand how it works. You can't say the same about someone who used an LLM who would need an LLM to continue working on the project and understand how it works. If the tool understands the code better than you and can't continue without it, you have essentially given up ownership.
The only caveat with my statement is that there are different degrees in which you can involve an LLM in your project but I mean if you are using it to write the majority of your code.
It is the same way a football fan thinks he helped his team win by watching on the sidelines while the players do the work and give you the illusion of participation.
Shouting racist slurs at the opposition, making monkey noises and throwing bananas is surely why my team won the match! Couldn’t have done it without us.
There is some evidence of that, where the closer the crowd is to the field the more likely the referees are to call in the home team's favour. There was a study on this, probably close to a decade ago now.
>Honestly I don’t expect these kind of low quality comment in HN. Where’s your thinking?
A comment that opens a discussion is not low quality just because you disagree with it Mr 7 karma. There is always a degree of irony with such statements.
You choosing the toppings for your pizza and whether you want cheese in your crust does not mean you made the pizza. You did not make it, you merely ordered it.
Wrong metaphor, because making a pizza involves other people.
A better metaphor would be:
A photocopier won’t copy documents by itself. If someone uses a machine to make a copy, they still made that exact copy. Whether that copy constitutes copyright infringement is a separate question.
Authorship still belongs to the user for AI outputs; their originality is debatable, though. These are two distinct concepts that people easily confuse.
Again, apply this reasoning to illegal AI-generated content: if humans are responsible for AI outputs, then they also have authorship of those outputs.
You’re denying another human’s authorship simply because they use a different tool from you.
Another angle you might argue is that you aren’t really “making” something unless you craft it directly. But then what about film directors, architects, or CEOs? Did they really make anything?
Again, you’re denying the role of human intention by gatekeeping the idea of “making” behind direct craft. That’s fine, but it’s a limited worldview.
I think this still leaves much of the concern the article points towards open. If we come across an objective that remains tedious or annoying, does AI create pressure towards thinking that it must not be a good objective and some AI-enabled objective would be better?
If it would be possible to walk to get groceries (and also exercise at the same time), do people choose to drive instead because it's simply easier and faster? They then claim that the goal of exercise is simply not worth it any more given driving is faster (and easier)?
I would say it more depends how the environment is designed and what transport options you have at your disposal.
In suburbia where the grocer is surrounded by a parking lot and there's busy roads to navigate nearby then of course people would drive rather than walk, and thus also end up getting a week's worth of groceries at a time.
In a dense mixed use environment where it is easy enough to navigate on foot then the urge to drive lessens and all grocery shopping can be done more frequently and on foot or by public transport.
I've experienced this personally in Australia, where living in suburbia I went grocery shopping once a week with a car and brought back many bags worth at a time, and also in a more dense neighbourhood where I could get groceries on the walk back from work more frequently and barely used my car even once a month. In Europe I only ever walk or get public transport for groceries as I live in a dense area and don't need to own a car.
Yes, absolutely they do. That's a huge contributing factor to why the obesity rate is so high in the US. I grew up about 10 minutes walking distance from a grocery store with a big parking lot and most of us in my neighborhood drove there.
- I (https://compile-xc.org) built a compiler for a language I call ‘xc’, similar to Objective-C but designed to be cross-platform and have less square brackets :). It can run on any of {Windows, Mac, Linux, Zynq} and produce code for any of {Windows, Mac, Linux, Zynq, WASM, iOS, Android, m68k, 6502}. It needs no host-platform tools to compile code, so for example I have a signed binary on my iPhone, written and signed entirely on Linux. The compiler currently produces code that is between 2x and 0.5x the speed of clang, which is pretty good for a nascent compiler. It also compiles the same language for execution on a GPU, and makes it trivial to designate parts of your code as data-parallel (https://compile-xc.org/compiler/language/par/). One statement turns a code block into a GPU kernel
- I built (more accurately: am building) a (https://compile-xc.org/compiler/api/uxkit) cross-platform UI framework, so you can write code once, even Table-views, Outline-views, Collection-views, etc., etc and your application will bind to the platform’s native toolkit through a common programming API. The next step here is an “Interface Builder” like application I call RoCkS (for historical reasons), which lets you design the UI for {desktop, tablet, phone} to bind to the same core code, dragging connections between that core code and the UI elements for the different environments
- I built (https://atari-xt.com/os) XTOS for the Zynq - an OS that started with FreeRTOS and added loadable processes, dynamic linking, shared memory, paging, a boot environment that can be scripted like Linux, networking, a graphical UI based on GEM, with a hardware blitter, and HDMI output with Audio islands mixed in. The blitter owns the video memory and uses shared-memory pools to give each “virtual workstation” (GEM-speak for “view of the display”) its own retained-mode and composited graphics memory. The whole OS boots from power-on to desktop in a couple of seconds, which is the reason for making it, rather than just using Linux, I wanted that “instant-on” feeling. It runs on a Z-turn board from MyIR.
- I built an Atari (6502, ANTIC, POKEY, various other chips) (https://atari-xt.com/hardware/x/)emulator, which passes the (https://forums.atariage.com/topic/171296-acid800-an-atari-te...) Acid 800 emulation torture test, and can run games such as Ballblazer, Elektraglide and (https://0x0000ff.co.uk/mov/xt/xtos-aug-11.mov)Despatch Rider. It’s integrated into XTOS, so the OS boots into the GEM-based Desktop.app (written in xc) and you can double-click an icon to launch a game. The plan is to extend that to the ST once I get past the current task, which is …
- I built a Reddit-like website that I plan to launch in a couple of months, written entirely in xc, both the Linux-based server and the client WASM code; the server-side is just xc code, no Apache, no scripting language, just lean-and-mean xc code handling everything from the TLS handshake to the Postgres database back-end. The main difference between (https://blewit.net/)blewit.net and Reddit is that I don’t collect any personal information, don’t track your habits and sell your data, don’t use adverts (tracking by another name) or any of the other dark patterns social media is infested with these days. Blewit is so named because I think they did. One of the other differentiators is that I plan to support the groups with specialist helpers. You can see a selection of them at (https://blewit.net/sandbox) the blewit sandbox - things like rendered music staves from ABC notation, 3d interactive molecules structure from SMILES notation, mathml with an editor to create it, etc, etc.
- One last purposely-separated “helper” from the others because of its scale, is the electronic circuit editor/simulator. I introduced it [url=https://www.eevblog.com/forum/projects/circuit-simulation-fo...]in the EEVBlog projects forum[/url], but no-one seemed to care [grin]. That’s a shame because I think it’s pretty cool, draw the circuit in the editor, you can create your own parts, even store them to a library, add digital logic to pins, import SPICE models, and simulate with ideal or oscilloscope-type probes. It understands transmission lines, tolerances, can run monte-carlo simulations, produce overlaid graphs for {R=1k, 4.7k, 10k} etc., I could go on. The full docs to it are in the (https://blewit.net/post/93083024324820992) Blewit editor-information pages
Overall, looking back at what using an LLM has helped me code over the last half-year or so, it is unbelievable what you can code with AI in 2026. I always used to say that I had too many ideas and not enough time to implement them, well that’s still true, but to a significantly lesser extent…
For all the above “I” is short for “I, with the help of Claude”
Maybe more like an architect saying "I built" when actually construction workers did all the building. Even that's stretching it though because construction workers tend to follow the plans fairly well. AI has you constantly tweaking the beams and cement yourself mid-construction to get a usable product.
Yes, it’s very similar to that, except the ic has no imagination, vision, or drive.
I wrote my first compiler about 35 years ago, and my first OS around the same time, well before LLMs were on the scene. I know exactly just how much work is involved with doing it well, which is why I’d never normally take on a project like this now I’m retired.
But we do not live in normal times. The language “I” have created (and it’s not as though I just said to Claude “hey, write me a compiler”) is (even if I say so myself) pretty cool. Here’s the full source of a Mandelbrot program:
#import "Stdio.xc"
#import "Par.xc"
#import "../src/include/bench_time.xc"
#define W 2048
#define SIZE (W * W)
i32 main(void)
{
// Eight runs: the first carries one-off costs (a GPU builds its kernel
// then), so the figure is the best run; the first is printed too. Auto
// decides after its fourth (two on each device), and uses the rest.
u32 total = 0;
i64 best = 0;
i64 first = 0;
for (u32 rep in 0..8)
{
total = 0;
i64 t0 = bench_now_us();
par mandel :reduce(+ total)
{
for (u32 i in 0..SIZE)
{
float cx = (float)(i % W) * (3.0f / 2048.0f) - 2.0f;
float cy = (float)(i / W) * (3.0f / 2048.0f) - 1.5f;
float x = 0.0f;
float y = 0.0f;
u32 k = 0;
while (k < 256 && x * x + y * y < 4.0f)
{
float xt = x * x - y * y + cx;
y = 2.0f * x * y + cy;
x = xt;
k = k + 1;
}
total = total + k;
}
}
i64 t1 = bench_now_us();
if (rep == 0)
first = t1 - t0;
if (rep == 0 || t1 - t0 < best)
best = t1 - t0;
}
Stdio.printf("%u %lld %lld\n", (total + 500000) / 1000000, best, first);
return 0;
}
Just one line in that source code is what turns it from a bog-standard C-like program into a GPU kernel, automatically tracked, scheduled, and all data hazards transparently managed.
On my M4 max, that one line of code takes it from 481ms to 1.6ms. All ‘par’ does is say “this next block of code, call it “mandel”, is data-parallel, and for the ‘total’ variable all execution units should combine their output to that variable using +
No huge GPU boilerplate, no stream management for data transport from cpu to gpu and back, no memory barriers, no hassle. Just “hey, do this on the gpu”.
GPU blocks are bound at runtime using the best design for the hardware on the machine, obtained by measuring it if it hasn’t been measured before. If it has, the cache is read. The user can always override, which is why ‘par’ blocks can be named.
Next up is an overlapping scheduler, which keeps 3 work units in play {pending, being-processed, being-transferred-once-done} for a processing device (right now, just a local gpu), which is also the multi-gpu story, and even the networked-machines story.
I think this is great work; these are strange times, i personally don't feel like i'm building stuff anymore, it is more like thinking it into existence
Schrödinger's AI: can't come up with ideas on its own and we'll all be doomed once we come to rely on it, but we shouldn't credit you with what you use it for; it's all just AI slop. Neat work.
Now that is funny, because I will die on this hill: I wrote every last word of that message - and to my eyes it doesn’t even read like an LLM wrote it.
People are way to quick to try to bring others down these days, unless there’s some subtle humour here I’m not getting.
:D added reddit clone to personal watch list. You are braver than me sharing this stuff on HN ( they can be ruthless when it comes to this stuff ). Nice work.
I’m satisfied that my actual engineering is up to snuff, done some pretty cool things over my career. Now I’m just having fun, and LLMs make it easier to have said fun :)
When faced with AI some companies are looking for employees to fire to achieve same goals cheaper. Other companies are looking how to uplift their employees to expand their capability and excelence.
Maybe the same thing happens at the level of individual persons. I think the difference is whether you felt limited or competent. If you felt competent you shrink. If you felt limited, you grow.
Exactly! The sheer effort of having AI produce good results, from writing, to planning, to coding is immense. I have consistently gather all my energies and focus to guide agents to the ideal, maintainable, and usable solution. Often it is me that makes the crucial design contribution.
Yes, I could be lazy and just vibe piles of slop. But anyone who spends any meaningful amount of time using AI (more than the articles 10 minutes), knows that quite extreme concentration and effort is required to build ambitiously with agents.
I feel like I work harder and and with more difficult problems than before AI, just at a much faster pace and scope.
Yes, thank you! This is exactly my experience. It requires immense effort and concentration, maybe more than before AI, where
- the next ideal step progressively manifested itself to me during coding
- I actually had perfect knowledge of the codebase and didn't have to work as hard to reconstruct it in my head each time
- coding itself is half a mechanical job. AI does the mechanical job itself well, leaving you only the hard thinking.
- AI prose isn't easy to parse, at least to ne.
- Prompting AI until it gets the optimal solution / implementation takes time and revisions.
Something like that.
I keep thinking that it's an issue of my approach, though. I've been trying to improve my AI workflow as much as possible for months, every day, but still, I'm not content with it. I might have gotten stuck on a local optimum. Maybe I'm writing prompts needlessly detailed. Maybe I should read more of the code, because I don't, really, making me not know the actual codebase and how things work.
It's not easy, this whole thing. And honestly, sometimes I wonder - after accounting for the total time, including revisions, mental reconstructions etc - if it wouldn't have been done faster by me in the pre-AI world.
