Using AI for just 10 minutes erodes your ability to persist at hard things
vcresearch.berkeley.edu
vcresearch.berkeley.edu
The evidence for reduced persistence is kinda weak.
The strongest experimental result in the paper is: if people use AI to help solve a series of problems, and then the AI is suddenly taken away, they perform worse on subsequent problems than people who hadn't been using AI for the earlier questions.
But:
- They're looking at really really short-term effects, like seconds or minutes. That's not really interesting if we care about long term effects (which is what the abstract says is important).
- What they found is totally expected and isn't something I'd worry about: it's kind of expected that if one guy warms up with 10 questions done himself, and the other guy warms up with 10 questions delegated to AI, then the second guy is going to do worse on the final 10 questions (because he didn't warm up).
Eventually you think you deserve to have the answer just handed to you without having done any of the work.
I agree with your general conclusion, but with this point, the solve rate for the AI group once AI is removed is lower than the initial solve rate for the other group in all the experiments (or at least definitely in 2 of 3), so I don't think it's explained by a warm-up.
From page 4:
Problem difficulty increased across the experiment from one-step1 (problems 1–4) to two-step2 (problems 5–8) to three-step3 (problems 9–12).
Problems increased in difficulty from one-step (problems 4-6) to two-step (problems 7-10) to three-step (problems 11-14) problems.
https://www.stuartmcmillen.com/comic/town-without-television...
And the IQs of those born after 1975 via the reverse Flynn Affect, those who had these devices of consumption and easy answers such as TV, and later Social Media, AI, etc has been decreasing.
I can only imagine a further and speedier decline will happen, and is happening.
What would they eat? Getting enough calories from hunting for it to become a frequent part of everyone's life is currently a thermodynamic impossibility. On top of that, food webs are actively collapsing or have already.
I've tried blocking specific sites from search results, but it's an unwinnable battle.
After that I'm left with a few seemingly-human-written web pages that relate to what I want to find.
I don't like it, but it works. For now.
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It's both amusing and frustrating that this is how Google used to work before they began filtering everything search-related through their own dumbest-of-bots. I know it's not 1998 anymore and that PageRank has been broken for a very long time and that the SEO war marches on in earnest. But it seems that the rate at which Google's search results become increasingly awful has been accelerating ~exponentially in the past few recent years.
Then you ignore everything the robot says, and just click the Wiki link (or journal article or whatever). Skimming the AI text and just finding the citations is the most important thing to do to save time with this method. You're only using it because it is good at ranking search results, not because you want a bad AI summary.
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)?
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.
> If it would be possible to walk to get groceries
It is.
> do people choose to drive instead because it's simply easier and faster?
Some. You also have to factor in the cost of gas (quite high) vs distance vs how much you plan to buy and possibly other factors (like discounts,...).
> They then claim that the goal of exercise is simply not worth it any more given driving is faster (and easier)?
I would think the goal is to get groceries, but yeah. People are quite lazy. The possibility of taking a car or a bus is always 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”
E.g.: I painted the Mona Lisa.
“I” meaning “I with the help of a JPEG on a computer and a color printer”.
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;
}
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’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 :)
People are way to quick to try to bring others down these days, unless there’s some subtle humour here I’m not getting.
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
Would you become unable to hunt?
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.
turn every supermarkt visit into a scavenger hunt?
oh, wait ...
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.
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.
Thats what $200 for a ticket to any N*L sunday football event buys you.
T-shirts are extra, and if we win, we sell more of them.
The hard working, professional, polite members of society benefit from the release I think.
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.
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.
If someone used AI and created something illegal(deepfake or whatever), can they claim it’s not their creation?
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.
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.
You can't convince me that shepherding an LLM to re-implement a library function involves less "engineering" than just... calling the function.
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.
- 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.
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.
We aren't all dead yet. (And we ain't just hunter-gatherers no more, neither!)
Or maybe instead: Someone has already done that and that is why we're not presently fucked.
Or, more realistically: The sky is not actually falling, just as it has also not fallen with any previous introduction of automation.
The risk if you ignore that is that you're on a nicely greased slope all the way down into the mess that a typical AI will leave behind.
I have a project right now that needs a lot of scaffolding to be worked on. I'm fine with the scaffolding and the mocks to be AI generated, they have no value to me at all. But the core gets written line-by-line by hand and I am in absolute control of what is going on there. The number of times that the AI has tried to gain control over that part of the codebase that it can't see but infers must be around somewhere is really interesting, it just does not want to stay in its lane. It will gaslight itself into believing that the root cause of whatever problem it is dealing with must be located in this magical invisible body of code and it will do what it can to try to find it, including attempts at reverse engineering that code from libraries and searching all over the accessible parts of the file system to see if there are any copies lying around.
Since I don't work at OpenAI I've found that containing the bot is rather easy, you just make sure it does not have network access, but that won't stop it from trying.
Or when your weekly limit hit. More fun if it's Tuesday. Say goodbye to the rest of week.
Participants are asked to drive 20 nails into a plank of wood. Group A is given a hammer and an unripe banana. Group B is given only a banana. Halfway through the experiment, the hammers are taken away.
Hammers erode your ability to persist at hard things…
My point being that AI is a new tool that allows us to work on harder things at a higher level. It’s like having a team of 100 skilled workers with nail guns (and all manner of other tools) that never tire, and you get to direct them. Once you experience that, it’s a bit disheartening to go back to building alone with your bare hands… even if you lament the decline in your hand-eye coordination.
Before AI, when building anything, you’d have to have a lot of context from different parts of the app. And then work with that knowledge to build the feature out in those places. Keeping that context in your head was tough and coming back the next day required you to “fill your internal RAM” with the context and then start.
Now we can use our “internal RAM” thinking about the bigger picture and bigger projects. We’ve just gone an abstraction layer deeper.
Art provides a counterpoint. The invention of cameras allowed you to capture reality in ways never seen before, and yet this lead to art having a _really weird_ few decades/century where artists rejected realism and instead embraced abstraction.
The difference between AI and no AI is like the difference between a hammer and a nail gun not a hammer and a banana.
If you have a nail gun you have to pay attention to what you are nailing together because it might rip through or the nail might stick out on the other side before you get a chance to pull it out and pick a shorter nail.
FWIW, well designed study probably would still support his premise. He at least needed a group with no help, a group with no help but books and a calculator (tools), a group with human assistance, and a group with AI assistance, and a group that does an unrelated activity during the priming period.
Our energy conservation system also encourages us to eat as much high fat, high sugar food as we can get down our gullets, but that turns out to be a big problem for modern humans.
Extremely Weak study.
I run Proxmox LXC containers at home managed via Ansible. I used Claude to assist me getting 4 services I was not familiar with working, draft the configuration, the firewall rule so all the traffic goes via a VPN and not my home network.
2 days and got everything working.
It took away what would have taken me a week reading posts after posts. Know that it is a tool to assist you and you will learn a lot from it. Posts/forums are kind gone right now.
I know Proxmox, I know Ansible, AI takes the boring part away and you have to think twice as much, not less. It gave me suggestions I didn't know was possible, therefore, you improve your skills.
Don't be copy/paste.
https://www.youtube.com/watch?v=Jt0OoXluC8g @ 4:08:
Writers disagree on what effect word processing will have on the quality of our written language.
Some writers are concerned that computer assistance may promote dry bland writing.
The time difference was measured in hours, not minutes, and and effort required to hand-saw is enormous. Also, the accuracy difference is ridiculous, even with a lot of practice, and maintaining that accuracy continues to be a struggle with hand-sawing.
I now own 6 different electric saws for different specific purposes. Table saw, chop saw, circular saw, track saw, jig saw, scroll saw... I actually probably have more. I got rid of my chainsaw because it lost its chain in a way that really scared me one day. I might get another some day, but not that one again. Does a Dremel count? I'm going to say 'no' so I don't have to count 2 of those.
And yet, I still own a 2 Japanese pull saws and a normal American hand saw. I don't use them as much, but some times they're still worth the effort.
When using table saw, you still need to make a lot of decision: The depth of cut, the angle, the length. If you don't make them, your project will not progress.
With AI, you can stop decide, tell the chat bot to do whatever they want and make any decision they like. Your ability to analyze problem and make decision is not practiced anymore and begin corroding.
I mean: In cabinetry, for instance, that's the kind of slop that dado joints help to hide and nobody ever knows about it after it's glued up.
And I'm not Norm Abram over here: I can can cheat even harder than that. I can get a sloppy six-sided wooden box to look nice and square with neat joints after basic assembly is done, using just a few minutes of time and a router with an appropriate bit.
It won't pass muster in even the most simple of metrological examinations, but I don't have to care about that. (And my work doesn't detract from that of Norm, either.)
Second, you make decision to be sloppy. That means you can also make decision to do it right. With AI, no matter how much "make no mistake" you scream toward it, no guarantee whatever it produces is high quality.
I made a decision to do it fast-er instead of perfect-er. I understand and embrace the results of this decision.
That's exactly my point here, you know it's sloppy. To know it's sloppy you must know what a good joint look like. Many vibecode projects the author even can't tell if their code is good or sloppy. Is it important, the ability to judge and decide something, depends on each individual, personally it's very important to me.
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Code. Despite this talk about woodworking (which I actually can accomplish with precision using a variety of tools when I elect to do that), I really can't write code for shit. I've been working on that for several decades and it's still just shit.
And I just don't care anymore.
I can feed stuff into the bot at a high level. And I can read code well-enough after all these decades of failure, so I can be hyper-critical of the results and produce precise demands for corrections. I can get resolutely-tight performance from it when it's important.
I once spent a lot of time working with the bot on RP2040 PIO assembly, where I was working with continuous high-speed signals. The RP2040 PIO has only a single-digit instruction count, a few registers, and just 32 instructions worth of memory. Individual clock cycles need counted, and slop doesn't work there at all. I accomplished what I needed to accomplish with perfection (as if it could ever be any other way). I'm pleased with the result, and I couldn't even have ever gotten started on that without the bot.
Some other times, I think that it's OK that it is slow or wasteful as long as the inputs eventually produce the right outputs. Like an intern who, when given a task to make a thing that implements a process comes back with something that's messy-but-working. It's not ideal, but it can be good enough some of the time.
I'm not fast at producing code with the bot and that doesn't matter to me: I'm getting things done (finished!) that I previously spent decades beating myself up about being unable to do. There are hardware+software things that are rolling right now and behaving themselves seemingly-perfectly that I wrote no code for at all; all I did was propose ideas, review the code where useful (because sometimes it's all fucked up), then discuss and implement changes.
Anyone can think of me as being stupider, somehow, than I used to be because of the addition of the bot into my life -- but I implore them to address that concern to me directly. I'm right here.
With AI, you can offload almost everything. With the saw, all I'm offloading is the cutting.
I don't actually have to make any decisions when doing woodworking. I can just buy some plans and follow them. The only time I need to make decisions is when I make something unique.
TBF, that's almost all the time for me.
But also TBF, it's the same with AI.
Sure, I can let it make all the decisions, but then I'm not going to end up with something uniquely mine. It's going to keep pulling back towards its training. To get what I want, I need to keep course-correcting the AI while building.
Some people are going to be fine with that, and will let is just make whatever it wants, and call it good enough. That's just like buying the plans and following them blindly.
The difference between tablesaws and AI is, like I said above, the range of things it can do. It's like having all the saws I listed above, plus electric screw drivers, drills, laser levels, and the whole rest of the toolkit, all in 1 box. You even get a chatbot that will tell all those things what to do to follow the plans.
Making good plans has always been one of the hardest parts of both woodworking and software development.
When you have half-arsed plans (in either discipline) you need to fix things up as you go, and that hasn't changed with AI.
AI removed a lot of the other hard things, but left the hard planning step, and the hard "hide the screwups" steps.
LLM let you focus on higher level, but LLM, to some degree, can also do higher level. Ask it "Design the architect of this software" and it will be happy to comply.
I've followed people using AI for a while now. At the beginning they are like you, write me a function that does this. They review every line of code. Then later they ask the LLM to write them a file, write them a module, etc. With the amount of code the LLM output, there is no practical way they review all of the code line by line. It's a slippery slope that require strict discipline and many people lack of that.
This feels similar. 10 minutes? So, after sever thousand hours of using AI to build projects, I can't solve hard problems? More nonsense.
I have to go now, the nurse here at the psychiatric ward is about to strap me down and give me my meds.
I'm still thinking, just about different things at different levels.
Did those tools make me stupid, too? (Can we do libraries next?)
This all reminds me of keruigs for some reason, like a quick easy way to get coffee that produces a lot of waste for a forgettable drink. I'm sort of advocating digital pour overs.
Since I started using AI seriously in my (mathematics) research about 6 weeks ago I've advanced more and been more productive than in years. I'm more motivated and persistent than before because I have at my disposal a tool that helps me get past technical obstacles that previously took up a lot of my time.
What is our cognitive fitness without our tools? How capable would we be at intellectual tasks if you remove computers, search engines and other things we now take for granted?
It's clear to me our overall output is better with those tools, and better with AI. So the comparison the paper is trying to make is disingenuous, because it tries to compare a baseline without any modern tools (ie, solving fractions by hand) to a result where the best tools are suddenly removed. But these tools are here to stay, and my cognitive fitness has adapted to their continued existence.
How well would these people doing fractions by hand perform if math notation could not be used? Or if the most common method for solving fractions on paper was suddenly disallowed?
How do you know trying hard isn’t stopping things from getting worse?
> If AI eases the burden even a little I'll take it.
It does ease the burden for a little bit but then makes the burden much harder when you don’t have it. That’s the point.
> Persistenting at hard things hasn't made my life any better yet.
Again, how do you know it’s not stopping it from getting worse? Also, are you sure you’re worrying about the right hard things?
Everything interesting enough to be worth doing is hard, and persisting at it is my most rewarding way to spend time.
If you took it away and made me loaf on a beach, I would enjoy it for about a day.
And then my life is empty and worthless and definitely not better. Even on that beach I would shortly be trying to make something interesting out of the palm leaves.
And then someon would say we should have a machine to do that because it's hard and "persisting at hard things hasn't made my life any better".
It's the most depressing sentiment I can imagine to say that.
Eg. I’m glad AI built my startups landing page in (almost) one prompt, because it’s allowed me to do the hard things that matter and I enjoy.