9 ms·

AI is a floor raiser, not a ceiling raiser

370 points by jjfoooo4 1y ago

bitwize 1y ago
AI is a shovel capable of breaking through the bottom of the barrel.
manyaoman 1y ago
AI is a wall raiser.
spullara 1y ago
[flagged]
- bugbuddy 1y ago
  Imagine how useful it would be we could just add a button show our approval or disapproval of a piece of content without having to type true or false in the comment section. Let’s call it upvote or downvote button. /s
  - crazygringo 1y ago
    I agree it wasn't a helpful comment. On the other hand, I don't know what this mythical downvote button for stories is you describe. I've certainly never seen it. Would be nice if HN actually had that.
    - falcor84 1y ago
      It's what "flag" is for: > Please don't complain that a submission is inappropriate. If a story is spam or off-topic, flag it. Don't feed egregious comments by replying; flag them instead. If you flag, please don't also comment that you did. https://news.ycombinator.com/newsguidelines.html https://news.ycombinator.com/newsguidelines.html
      - dns_snek 1y ago
        This article is neither spam nor off topic.
        falcor84 1y ago
        I would agree, and have personally enjoyed the article. I just assumed that the person who wrote "false" might have considered it to be spam (perhaps in the broader sense), and if they did, flagging is considered to be the proper way of showing their disagreement.
      - crazygringo 1y ago
        No it's not. There are a lot of stories that aren't worthy of flagging, but they're just low-quality. And I've seen people abuse flagging because they treat it like downvoting. Flagging removes a story from the front page entirely, whereas ideally downvoting would simply deprioritize it, i.e. a bunch of downvotes would move it from #5 rank to #60 or something, not get rid of it entirely. I've definitely had to e-mail the mods a number of times to restore a flagged story that was entirely appropriate, but which a few users simply didn't like. It would be much better to have a downvote button, and reserve flagging for actual spam and inappropriate content.
        spullara 1y ago
        i have seen a lot of speculation about my "false" comment on this story. i think the story is bullshit and AI 100% it raises the ceiling and doesn't help incompetent people that much. you see it over and over where incompetent people use AI and submit legal docs with hallucinations or have egregious security holes in their vibe coded projects. but i have seen highly skilled folks get month long projects done in a day with higher quality, more tests and more features than they would in the past. explaining all that didn't seem necessary since the whole thing is just not true.
amelius 1y ago
AI is an interpolator, not an extrapolator.
- throe23486 1y ago
  I read this as interloper. What's an extraloper?
  - exasperaited 1y ago
    Opposite of "inter-" is "intra-". Intraloper, weirdly enough, is a word in use.
    - djeastm 1y ago
      So we have also have the word "extra", but oddly the word "exter" is left out. I'm exter mad about that.
    - jjk166 1y ago
      "inter-" means between, "intra-" means within, "extra-" means outside. "intra-" and "inter" aren't quite synonyms but they definitely aren't opposites of eachother.
      - exasperaited 1y ago
        Inter- implies relationships between entities, intra- implies relationships within entities. In any single sentence context they cannot refer to the same relationships, and that which they are not is precisely the domain of the other word: they are true antonyms.
        jjk166 1y ago
        > and that which they are not is precisely the domain of the other word External relationships are a thing, which are in neither of those domains. An intramural activity is not the same thing as an intermural activity, but the overwhelming majority of activities which are not intramural activities are not intermural activities either, most are extramural activities.
lupire 1y ago
OP doesn't understand that almost everything is neither at the floor or the ceiling.
givemeethekeys 1y ago
AI is a floor destroyer not a ceiling destroyer. Hang on for dear life!! :P
bfigares 1y ago
AI raises everything - the ceiling is just being more productive. Productivity comes from adequacy and potency of tools. We got a hell of a strong tool in our hands, therefore, the more adequate the usage, the higher the leverage.
- infecto 1y ago
  Surprised to see this downvoted. It feels true to me. Sure there are definitely novel areas where folks might not benefit but I can see a future where this tool becomes helpful for the vast majority of roles.
andrenotgiant 1y ago
This tracks for other areas of AI I am more familiar with. Below average people can use AI to get average results.
- itsoktocry 1y ago
  That explains why people here are against it, because everyone is above average I guess.
  - falcor84 1y ago
    I'm not against it. I wonder where in the distribution it puts me.
    - leptons 1y ago
      At the "Someone willing to waste their time with slop" end?
      - falcor84 1y ago
        Seeing that it gives me code that I then then use, then it's not a waste of my time.
        leptons 1y ago
        A broken clock is right twice a day. If you're spending more time writing instructions for the AI, and then rewriting those instructions several times before you get usable code, then you're absolutely wasting your time. At least this is my experience with "AI". Even the fancy autocomplete portion of "AI" gets in my way more than it helps. Of course, YMMV, but I seriously doubt you're doing any better with "AI" than anyone else actually is, and a lot of people using it just don't realize all the time it's wasting, if they paid attention and added it all up.
- pcrh 1y ago
  This is in line with another quip about AI: You need to know more than the LLM in order to gain any benefit from it.
erlend_sh 1y ago
Only for the people already affluent enough to afford the ever-more expensive subscriptions. Those most in need of a floor-raising don’t have the disposable income to take a bet on AI.
- intended 1y ago
  Either you are the item being sold or you are paying for the service. Nothing is free, and I for one prefer a subscription model, if only as a change from the ad model. I am sure we will see the worst of all worlds, but for now, for this moment in history, subscription is better than ads. Let’s also never have ads in GenAi tools. The kind of invasive intent level influence these things can achieve, will make our current situation look like a paradise
  - quirkot 1y ago
    I'd never buy anything as overt as an advertisement in an AI tool. I just want to buy influence. Just coincidentally use my product as the example. Just suggest my preferred technology when asked a few % more often than my competitors. I'd never want someone to observe me pulling the strings
  - LtWorf 1y ago
    Normally even if you pay you're still the product anyway. See buying smartphones for example… you pay a lot but you're the product.
- pdntspa 1y ago
  It's very easy to sign up for an API account and pay per-call, or even nothing. Free offerings out there are great (Gemini, OpenRouter...) and a few are even suitable for agentic development.
  - LtWorf 1y ago
    And how long until they raise the prices?
recroad 1y ago
AI isn't a pit. AI is a ladder.
- anthk 1y ago
  Yeah, like in Nethack, while being blind and stepping on a cockatrice.
- layer8 1y ago
  A ladder that doesn't reach the ceiling and sometimes ends up in imaginary universes.
billyp-rva 1y ago
Mixing this with a metaphor from earlier: giving a child a credit card is also a floor raiser.
manmal 1y ago
Since agents are good only at greenfield projects, the logical conclusion is that existing codebases have to be prepared such that new features are (opinionated) greenfield projects - let all the wiring dangle out of the wall so the intern just has to plug in the appliance. All the rest has to be done by humans, or the intern will rip open the wall to hang a picture.
- PaulHoule 1y ago
  Hogwash. If you can't figure out how to do something with project Y from npm try checking it out from Github with WebStorm and asking Junie how to do it -- often you get a good answer right away. If not you can ask questions that can help you understand the code base. Don't understand some data structure which is a maze of Map<String, Objects>(s) it will scan how it is used and give you draft documentation. Sure you can't point it to a Jira ticket and get a PR but you certainly can use it as a pair programmer. I wouldn't say it is much faster than working alone but I end up writing more tests and arguing with it over error handling means I do a better job in the end.
  - falcor84 1y ago
    > Sure you can't point it to a Jira ticket and get a PR You absolutely can. This is exactly what SWE-Bench[0] measures, and I've been amazed at how quickly AIs have been climbing those ladders. I personally have been using Warp [1] a lot recently and in quite a lot of low-medium difficulty cases it can one-shot a decent PR. For most of my work I still find that I need to pair with it to get sufficiently good results (and that's why I still prefer it to something cloud-based like Codex [2], but otherwise it's quite good too), and I expect the situation to flip over the coming couple of years. [0] https://www.swebench.com/ https://www.swebench.com/ [1] https://www.warp.dev/ https://www.warp.dev/ [2] https://openai.com/index/introducing-codex/ https://openai.com/index/introducing-codex/
    - esafak 1y ago
      How does Warp compare to others you have tried?
BoredPositron 1y ago
AI is chairs.
- furyofantares 1y ago
  I feel like nobody remembers that facebook ad (Facebook is chairs), but it's seared into my own memory.
  - anon35 1y ago
    https://www.youtube.com/watch?v=SSzoDPptYNA&t=53s https://www.youtube.com/watch?v=SSzoDPptYNA&t=53s
msgodel 1y ago
You'll find many people lack the willpower and confidence to even get on the floor though. If it weren't for that they'd already know a programming language and be selling something.
TimPC 1y ago
People should be worried because right now AI is on an exponential growth trajectory and no-one knows when it will level off into an s-curve. AI is starting to get close to good enough. If it becomes twice as good in seven months then what?
- mattnewport 1y ago
  What's the basis for your claim that it is on an exponential growth trajectory? That's not the way it feels to me as a fairly heavy user, it feels more like an asymptotic approach to expert human level performance where each new model gets a bit closer but is not yet reaching it, at least in areas where I am expert enough to judge. Improvements since the original ChatGPT don't feel exponential to me.
  - samsartor 1y ago
    This also tracks with my experience. Of course, technical progress never looks smooth through the steep part of the s-curve, more a sequence of jagged stair-steps (each their own little s-curve in miniature). We might only be at the top of a stair. But my feeling is that we're exhausting the form-factor of LLMs. If something new and impressive comes along it'll be shaped different and fill a different niche.
- nwienert 1y ago
  Let's look: GPT-1 June 2018 GPT-2 February 2019 GPT-3 November 2021 GPT-4 March 2023 Claude tells me this is the rough improvement of each: GPT-1 to 2: 5-10x GPT-2 to 3: 10-20x GPT 3 to 4: 2-4x Now it's been 2.5 years since 4. Are you expecting 5 to be 2-4x better, or 10-20x better?
  - esafak 1y ago
    How are you measuring this improvement factor? We have numerous benchmarks for LLMs and they are all saturating. We are rapidly approaching AGI by that measure, and headed towards ASI. They still won't be "human" but they will be able to do everything humans can, and more.
LeftHandPath 1y ago
There are some things that you still can't do with LLMs. For example, if you tried to learn chess by having the LLM play against you, you'd quickly find that it isn't able to track a series of moves for very long (usually 5-10 turns; the longest I've seen it last was 18) before it starts making illegal choices. It also generally accepts invalid moves from your side, so you'll never be corrected if you're wrong about how to use a certain piece. Because it can't actually model these complex problems, it really requires awareness from the user regarding what questions should and shouldn't be asked. An LLM can probably tell you how a knight moves, or how to respond to the London System. It probably can't play a full game of chess with you, and will virtually never be able to advise you on the best move given the state of the board. It probably can give you information about big companies that are well-covered in its training data. It probably can't give you good information about most sub-$1b public companies. But, if you ask, it will give a confident answer. They're a minefield for most people and use cases, because people aren't aware of how wrong they can be, and the errors take effort and knowledge to notice. It's like walking on a glacier and hoping your next step doesn't plunge through the snow and into a deep, hidden crevasse.
- smiley1437 1y ago
  > people aren't aware of how wrong they can be, and the errors take effort and knowledge to notice. I have friends who are highly educated professionals (PhDs, MDs) who just assume that AI\LLMs make no mistakes. They were shocked that it's possible for hallucinations to occur. I wonder if there's a halo effect where the perfect grammar, structure, and confidence of LLM output causes some users to assume expertise?
  - bayindirh 1y ago
    Computers are always touted as deterministic machines. You can't argue with a compiler, or Excel's formula editor. AI, in all its glory, is seen as an extension of that. A deterministic thing which is meticulously crafted to provide an undisputed truth, and it can't make mistakes because computers are deterministic machines. The idea of LLMs being networks with weights plus some randomness is both a vague and too complicated abstraction for most people. Also, companies tend to say this part very quietly, so when people read the fine print, they get shocked.
tayo42 1y ago
I was thinking about this sentiment on my long car drive today. it feels like when you need to paint walls in your house. If you've never done it before you'll probably reach for tape to make sure you don't ruin the ceiling and floors. the tape is a tool for amateur wall painters to get decent results somewhat efficiently compared to if they didn't. If your an actual good wall painter, tape only slows you down. You'll go faster without the "help".
stillpointlab 1y ago
This mirrors insights from Andrew Ng's recent AI startup talk [1]. I recall he mentions in this video that the new advice they are giving to founders is to throw away prototypes when they pivot instead of building onto a core foundation. This is because of the effects described in the article. He also gives some provisional numbers (see the section "Rapid Prototyping and Engineering" and slides ~10:30) where he suggests prototype development sees a 10x boost compared to a 30-50% improvement for existing production codebases. This feels vaguely analogous to the switch from "pets" to "livestock" when the industry switched from VMs to containers. Except, the new view is that your codebase is more like livestock and less like a pet. If true (and no doubt this will be a contentious topic to programmers who are excellent "pet" owners) then there may be some advantage in this new coding agent world to getting in on the ground floor and adopting practices that make LLMs productive. 1. https://www.youtube.com/watch?v=RNJCfif1dPY https://www.youtube.com/watch?v=RNJCfif1dPY
- falcor84 1y ago
  Great point, but just mentioning (nitpicking?) that I never heard about machines/containers referred to as "livestock", but rather in my milieu it's always "pets" vs "cattle". I now wonder if it's a geographical thing.
  - HPsquared 1y ago
    Boxen? (Oxen)
    - bayindirh 1y ago
      AFAIK, Boxen is a permutation of Boxes, not Oxen.
      - mananaysiempre 1y ago
        There seems to be a pattern of humorous plurals in English where by analogy with ox ~ oxen you get -x ~ -xen: boxen, Unixen, VAXen. Before you call this pattern silly, consider that the fairly normal plural “Unices” is by analogy with Latin plurals in -x = -c|s ~ -c|ēs, where I’ve expanded -x into -cs to make it clear that the Latin singular comprises a noun stem ending in -c- and a (nominative) singular ending -s, which does exist in Latin but is otherwise completely nonexistent in English. (This is extra funny for Unix < Unics < Multics.) Analogies are the order of the day in this language.
bluefirebrand 1y ago
AI is not a floor raiser It is a false confidence generator
- burnt-resistor 1y ago
  It seems most suitable as an autonomous political speech writer and used car salesman coach.
falcor84 1y ago
I agree with most of TFA but not this: > This means cheaters will plateau at whatever level the AI can provide From my experience, the skill of using AI effectively is of treating the AI with a "growth mindset" rather than a "fixed" one. What I do is that I roleplay as the AI's manager, giving it a task, and as long as I know enough to tell whether its output is "good enough", I can lend it some of my metagcognition via prompting to get it to continue working through obstacles until I'm happy with the result. There are diminishing returns of course, but I found that I can get significantly better quality output than what it gave me initially without having to learn the "how" of the skill myself (i.e. I'm still "cheating"), and only focusing my learning on the boundary of what is hard about the task. By doing this, I feel that over time I become a better manager in that domain, without having to spend the amount of effort to become a practitioner myself.
- tailspin2019 1y ago
  I wouldn’t classify what you’re doing as “cheating”!
- righthand 1y ago
  How do you know it’s significantly better quality if you don’t know any of the “how”? The quality increase seems relative to the garbage you start with. I guess as long as you impress yourself with the result it doesn’t matter if it’s not actually higher quality.
  - razzmatazmania 1y ago
    I don't think "quality" has anything like a universal definition, and when people say that they probably mean an alignment with personal taste. Does it solve the problem? As long as it isn't prohibitively costly in terms of time or resources, then the rest is really just taste. As a user I have no interest whatsoever if your code is "idiomatic" or "modular" or "functional". In other industries "quality" usually means free of defects, but software is unique in that we just expect products to be defective. Your surgeon operates on the wrong knee? The board could revoke the license, and you are getting a windfall settlement. A bridge design fails? Someone is getting sued or even prosecuted. SharePoint gets breached? Well, that's just one of those things, I guess. I'm not really bothered that AI is peeing in the pool that has been a sewer as long as I can remember. At least the AI doesn't bill at an attorney's rate to write a mess that barely works.
fellowniusmonk 1y ago
The greatest use of LLMs is the ability to get accurate answers to queries in a normalized format without having to wade through UI distraction like ads and social media. It's the opposite of finding an answer on reddit, insta, tvtropes. I can't wait for the first distraction free OS that is a thinking and imagination helper and not a consumption device where I have to block urls on my router so my kids don't get sucked into a skinners box. I love being able to get answers from documentation and work questions without having to wade through some arbitrary UI bs a designer has implemented in adhoc fashion.
- leptons 1y ago
  I don't find the "AI" answers all that accurate, and in some cases they are bordering on a liability even if way down below all the "AI" slop it says "AI responses may include mistakes". >It's the opposite of finding an answer on reddit, insta, tvtropes. Yeah it really is because I can tell when someone doesn't know the topic well on reddit, or other forums, but usually someone does and the answer is there. Unfortunately the "AI" was trained on all of this, and the "AI" is just as likely to spit out the wrong answer as the correct one. That is not an improvement on anything. > wade through UI distraction like ads and social media Oh, so you think "AI" is going to be free and clear forever? Enjoy it while it lasts, because these "AI" companies are in way over their heads, they are bleeding money like their aorta is a fire hose, and there will be plenty of ads and social whatever coming to brighten your day soon enough. The free ride won't go on forever - think of it as a "loss leader" to get you hooked.
  - margalabargala 1y ago
    I agree with the whole first half, but I disagree that LLM usage is doomed to ad-filled shittyness. AI companies may be hemmoraging money, but that's because their product costs so much to run; it's not like they don't have revenue. The thing that will bring profitability isn't ads, it will be innovations that let current-gen-quality LLMs run at a fraction of the electricity and power cost. Will some LLMs have ads? Sure, especially at a free tier. But I bet the option to pay $20/month for ad-free LLM usage will always be there.
gruez 1y ago
The blog post has a bunch of charts, which gives it a veneer of objectivity and rigor, but in reality it's just all vibes and conjecture. Meanwhile recent empirical studies actually point in the opposite direction, showing that AI use increases inequality, not decrease it. https://www.economist.com/content-assets/images/20250215_FNC938.png https://www.economist.com/content-assets/images/20250215_FNC... https://www.economist.com/finance-and-economics/2025/02/13/how-ai-will-divide-the-best-from-the-rest https://www.economist.com/finance-and-economics/2025/02/13/h...
- Calavar 1y ago
  The graphic has four studies that show increased inequality and six that show reduced inequality.
  - gruez 1y ago
    Read my comment again. keyword here is "recent". The second link also expands on why it's relevant. It's best to read the whole article, but here's a paragraph that captures the argument: >The shift in recent economic research supports his observation. Although early studies suggested that lower performers could benefit simply by copying AI outputs, newer studies look at more complex tasks, such as scientific research, running a business and investing money. In these contexts, high performers benefit far more than their lower-performing peers. In some cases, less productive workers see no improvement, or even lose ground.
    - jjk166 1y ago
      All of the studies were done 2023-2024 and are not listed in order that they were conducted. The studies showing reduced equality all apply to uncommon tasks like material discovery and debate points, whereas the ones showing increased equality are broader and more commonly applicable, like writing, customer interaction, and coding.
      - deleted 1y ago
        [deleted]
verelo 1y ago
Oh man i love this take. It's how I've been selling what I do when I speak with a specific segment of my audience: "My goal isn't to make the best realtors better, it's to make the worst realtors acceptable". And my client is often the brokerage, they just want their agents to produce commissions so they make a cut. They know their top producers probably wont get much from what I offer, but we all see that their worst performers could easily double their business.
cropher 1y ago
Really liked this article. I wonder: the graphs treat learning with and without AI as two different paths. But obviously people can switch between learning methods or abandon one of them. Then again, I wonder how many people go from learning about a topic using LLMs to then leaving them behind to continue the old school way. I think the early spoils of LLM usage could poison your motivation to engage with the topic on your own later on.
- serial_dev 1y ago
  I learn about different subjects mixing traditional resources and AI. I can watch a video about the subject, when I want to go deeper, I go to LLMs, throw a bunch of questions at it, because thanks to the videos I now know what to ask. Then the AI responses tell me what I need to understand deeper, so I pick a book that addresses those subjects. Then as I read the book and I don’t understand something, or I have some questions that I want the answer for immediately, I consult ChatGPT (or any other tool I want to try). At different points in the journey, I find something I could build myself to deepen my understanding. I google open source implementations, read them, ask LLMs again, I watch summary videos, and work my way through the problem. LLMs serve as a “much better StackOverflow / Google”.
  - bloomca 1y ago
    I use a similar approach. I tried to experiment going into a topic with no knowledge and it kinda fumbles, I highly recommend to have an overview. But once you know basics, LLMs are really good to deepen the knowledge, but using only them is quite challenging. But as a complementary tool I find them excellent.
precompute 1y ago
I'd argue that AI reduces the distance between the floor and the ceiling, only both the floor and ceiling move -- the floor moves up, the ceiling downwards. Just using AI makes the floor move up, while over-reliance on it (a very personal metric) pushes the ceiling downwards. Unlike the telephone (telephones excited a certain class of people into believing that world-wide enlightenment was on their doorstep), LLMs don't just reduce reliance on visual tells and mannerisms, they reduce reliance on thinking itself. And that's a very dangerous slope to go down on. What will happen to the next generation when their parents supply substandard socially-computed results of their mental work (aka language)? Culture will decay and societal norms will veer towards anti-civilizational trends. And that's exactly what we're witnessing these days. The things that were commonplace are now rare and sometimes mythic. Everyone has the same number of hours and days and years. Some people master some difficult, arcane field while others while it away in front of the television. LLMs make it easier for the television-watchers to experience "entertainment nirvana" while enticing the smart, hard-workers to give up their toil and engage "just a little" rest, which due to the insidious nature of AI-based entertainment, meshes more readily with their more receptive minds.
guywithahat 1y ago
Wouldn't it be both by this definition? It raises the bar for people who maybe have a lower IQ ("mastery"), but people who can us AI can then do more than ever before, raising the ceiling as well.
- kruffalon 1y ago
  Wouldn't "more" in this house metaphor be like expanding the floor rather than raising the ceiling?
sabaimran 1y ago
In things that I am comparatively good at (e.g., coding), I can see that it helps 'raise the ceiling' as a result of allowing me to complete more of the low level tasks more effectively. But it is true as well that it hasn't raised my personal bar in capability, as far as I can measure. When it comes to things I am not good at at, it has given me the illusion of getting 'up to speed' faster. Perhaps that's a personal ceiling raise? I think a lot of these upskilling utilities will come down to delivery format. If you use a chat that gives you answers, don't expect to get better at that topic. If you use a tool that forces you to come up with answers yourself and get personalized validation, you might find yourself leveling up.
- spartanatreyu 1y ago
  > When it comes to things I am not good at at, it has given me the illusion of getting 'up to speed' faster. Perhaps that's a personal ceiling raise? Disagree. It's only the illusion of a personal ceiling raise. --- Example 1: Alice has a simple basic text only blog. She wants to update the styles on his website, but wants to keep his previous posts. She does research to learn how to update a page's styles to something more "modern". She updates the homepage, post page, about page. She doesn't know how to update the login page without breaking it because it uses different elements she hasn't seen before. She does research to learn what the new form elements and on the way sees recommendations on how to build login systems. She builds some test pages to learn how to restyle forms and while she's at it, also learns how to build login systems. She redesigns her login page. Alice believes she has raised the ceiling what she can accomplish. Alice is correct. --- Example 2: Bob has a simple basic text only blog. He wants to update the styles on his website, but wants to keep his previous posts. He asks the LLM to help him update styles to something more "modern". He updates the homepage, post page, about page, and login page. The login page doesn't work anymore. Bob asks the LLM to fix it and after some back and forth it works again. Bob believes she has raised the ceiling what he can accomplish. Bob is incorrect. He has not increased his own knowledge or abilities. A week later his posts are gone. --- There are only a few differences between both examples: 1. Alice does not use LLMs, but Bob does. 2. Alice knows how to redesign pages, but Bob does not. 3. Alice knows how login systems work, but Bob does not. Bob simply asked the LLM to redesign the login page, and it did. When the page broke, he checked that he was definitely using the right username and password but it still wasn't working. He asked the LLM to change the login page to always work with his username and password. The LLM produced a login form that now always accepted a hard coded username and password. The hardcoded check was taking place on the client where the username and password were now publicly viewable. Bob didn't ask the LLM to make the form secure, he didn't even know that he had to ask. He didn't know what any of the footguns to avoid were because he didn't even know there were any footguns to avoid in the first place. Both Alice and Bob started from the same place. They both lacked knowledge on how login systems should be built. That knowledge was known because it is documented somewhere, but it was unknown to them. It is a "known unknown". When Alice learned how to style form elements, she also read links on how forms work which lead her to links on how login systems work. That knowledge for her went from an unknown known to a "known known" (knowledge that is known, that she now also knows). When Bob asked the LLM to redesign his login page, at no point in time does the knowledge of how login systems work become a "known known" for him. And a week later some bored kid finds the page, right clicks on the form, clicks inspect and sees a username and password to log in with.
resters 1y ago
AI will be both a floor and a ceiling raiser, since there is a practical limit to how many domains one person or team can be expert in, and AI does/will have very strong levels of expertise/competency across a large number of domains and will thus offer significant level-ups in areas where cross-domain synthesis is crucial or where the limits of human working memory and pattern recognition make cross-domain synthesis unlikely to occur. AI also enables much more efficient early stage idea validation, the point at which ideas/projects are the least anchored in established theory/technique. Thus AI will be a great aid in idea generation and early stage refinement, which is where most novel approaches stall or sit on a shelf as a hobby project because the progenitor doesn't have enough spare time to work through it.
righthand 1y ago
It’s definitely about wage stagnation.
- burnt-resistor 1y ago
  Wage suppression. The capital ownership class knows exactly how to weaponize the hype as an excuse now. It's also curious how software engineers working on it are cheerfully building their potential future replacements and long-term insecurity.
buffzebra 1y ago
Only the first two mastery-time graphs make sense.
resters 1y ago
AI is going to cause a regression to the most anodyne output across many industries. As humans who had to develop analytical skills, writing skills, etc., we struggle to imagine the undeveloped brains of those who come of age in the zero-intellectual-gravity world of AI. OpenAI's study mode is at best a fig leaf. edit: this comment was posted tongue-in-cheek after my comment reflecting my actual opinion was downvoted with no rebuttals: https://news.ycombinator.com/item?id=44749957 https://news.ycombinator.com/item?id=44749957
- elcritch 1y ago
  I would say the modern digital world itself has already had the bigger impact on human thinking, at least at work. It seems with computers we often think and reason far less than without. Everything required thought previously, now we can just copy and paste out word docs for everything. PowerPoints are how key decisions are communicated in most professional settings. Before modern computers and especially the internet we also had more time for deep thinking and reasoning. The sublimity of deep thought in older books amazes me and it feels like modern authors are just slightly less deep on average. So then LLMs are in my view an incremental change rather than a stepwise change with respect to its effects on human cognitive. In some ways LLMs allow us to return a bit to more humanistic deep thinking. Instead of spending hours looking up minutia on Google, StackOverflow, etc now we can ask our favorite LLM instead. It gives us responses with far less noise. Unlike with textbooks we can have dialogues and have it take different perspectives. Whereas textbooks only gave you that authors perspective. Of course, it’s up to individuals to use it well and as a tool to sharpen thinking rather than replace it.
michaelhoney 1y ago
I think all of this is true, but the shape of the chart changes as AI gets better. Think of how a similar chart for chess/go/starcraft-playing proficiency has changed over the years. There will come a time when the hardest work is being done by AI. Will that be three years from now or thirty? We don't know yet, but it will come.
dcchambers 1y ago
I mean it makes sense that if the AI is trained on human-created things it can never actually do better than that. Can't bust through the ceiling of what it was trained on. And at the same time, it AI gives that power to people that just aren't very smart or good at something.
m3kw9 1y ago
At the very least
Madmallard 1y ago
I guess the AI glazing has infiltrated everywhere
godelski 1y ago
I think a good way to see it is "AI is good for prototyping. AI is not good for engineering" To clarify, I mean that the AI tools can help you get things done really fast but they lack both breadth and depth. You can move fast with them to generate proofs of concept (even around subproblems to large problems), but without breadth they lack the big picture context and without depth they lack the insights that any greybeard (master) has. On the other hand, the "engineering" side is so much more than "things work". It is about everything working in the right way, handling edge cases, being cognizant of context, creating failure modes, and all these other things. You could be the best programmer in the world, but that wouldn't mean you're even a good engineer (in real world these are coupled as skills learned simultaneously. You could be a perfect leetcoder and not helpful on an actual team, but these skills correlate). The thing is, there will never be a magic button that a manager can press to engineer a product. The thing is, for a graybeard most of the time isn't spent around implementation, but design. The thing is, to get to mastery you need experience, and that experience requires understanding of nuanced things. Things that are non-obvious. There may be a magic button that allows an engineer to generate all the code for codebase, but that doesn't replace engineers. (I think this is also a problem in how we've been designing AI code generators. It's as if they're designed for management to magically generate features. The same thing they wish they could do with their engineers. But I think the better tool would be to focus on making a code generator that would generate based on an engineer's description. I think Dijkstra's comments apply today just as much as they did then[0] [0] On the foolishness of "natural language programming" https://www.cs.utexas.edu/~EWD/transcriptions/EWD06xx/EWD667.html https://www.cs.utexas.edu/~EWD/transcriptions/EWD06xx/EWD667...
- per1Peteia 1y ago
  I was reading some stuff by Michael A. Jackson (Problem Frames Approach) and T.S.E Maibaum (Mathematical Foundations on Software Engineering) because I also had the impression that too much talk around LLM-assisted programming focuses on program text and annotations / documentation. Thinkers like Donald Schön thought about tacit knowledge-in-action and approached this with design philosophy. when looking at LLM-assisted programming, I call this shaded context. as you say, software engineering is not only constructing program texts, its not even only applied math or overly scientific. at least that is my stance. I suspect AI code editors have lots of said tacit knowledge baked in (via the black box itself or its engineers) but we would be better off thinking about this explicitly.
BrenBarn 1y ago
In one sense it's a floor-lowerer, since it lowers the floor on how clueless you can be and still produce something loosely describably as software.
atlgator 1y ago
I'm not sure this is my experience so far. What I'm noticing is that my awesome developers have embraced AI as an accelerator, particularly for research and system design, small targeted coding activities with guardrails. My below average developers are having difficulty integrating AI at all in their workflow. If this trend continues the chasm between great and mediocre devs will widen dramatically.
PeterStuer 1y ago
Most non-trivial expertise topics are not one-dimensional. You might be at the "ceiling" in some particular sub-niche, while still on the floor on other aspects of the topic. So even if you follow the artcles premise (I do not), it still can potentially 'raise' you wherever you were. Key seems to be wether you have enough expertise to evaluate or test the outputs. Some others have refered to this as having a good sense of the "known/unknown" matrix for the domain. The AI will be most helpful for you in the known-unknown / unknown-known axis, not so much in the known-known / unknown-unknown parts. The latter unfortunatly is were you see the most derailed use of the tech.
ygritte 1y ago
At least the last coding-with-AI chart is still too optimistic, I think. It doesn't reflect how AI coding tools are making developers less productive (instead of more) in non-trivial projects.
rnaarten 1y ago
The blog still assumes that AI does not affect Mastery. I think it does. All the AI junk like Agents in Service centers that you need to outplay in order to get in touch with a human, us as consumers are accepting this new status quo. We will accept products that sometimes can do crazy stuff because of hallucinations. Why? Ultimate capitalism consumerism sheepism, some other ism. So AI (and whether it is correlarion or causation, i dont know) also corresponds with lower level of Mastery
conartist6 1y ago
The learning-with-AI curve should cross back under the learning-without-AI curve at towards the higher end even without "cheating". The very highest levels of mastery can only come from slow, careful, self-directed learning that someone in a hurry to speedrun the process isn't focusing on.
careful_ai 1y ago
[dead]
mensetmanusman 1y ago
The second derivative of floor raiser is ceiling raising.
nunez 1y ago
So speaking of "mastery": I wanted to know how to clone a single folder in a Git repository. Having done this before, I knew that there was some incantation I needed to make to the git CLI to do it, but I couldn't remember what it was. I'm very anti-AI for a number of reasons, but I've been trying to use it here and there to give it the benefit of the doubt and avoid becoming a _complete_ dinosaur. (I was very anti-vim ages ago when I learned emacs; I spent two weeks with vim and never looked back. I apply this philosophy to almost everything as a result.) I asked Qwen3-235B (reasoning) via Kagi Assistant how I could do this. It gave me a long block of text back that told me to do the thing I didn't want it to do: mkdir a directory, clone into it, move the directory I wanted into the root of the directory, delete everything else. When I asked it if it was possible to do this without creating the directory, it, incorrectly, told me that it was not. It used RAG-retrieved content in its chain of thought, for what that's worth. It took me only 30 seconds or so to find the answer I wanted on StackOverflow. It was the second most popular answer in the thread. (git clone --filter=tree: --depth=0, then git sparse-checkout set --no-cone $FOLDER, found here: https://stackoverflow.com/a/52269934 https://stackoverflow.com/a/52269934) I nudged the Assistant a smidge more by asking it if there was a subcommand I could use instead. It, then, suggested "sparse-checkout init", which, according to the man page for this subcommand, is deprecated in favor of "set". (I went to the man page to understand what the "cone" method was and stumbled on that tidbit.) THIS is the thing that disappoints me so much about LLMs being heralded as the next generation of search. Search engines give you many, many sources to guide you to the correct answer if you're willing to do the work. LLM services tell you what the "answer" is, even if it's wrong. You get potential misinformation back while also turning your brain off and learning less; a classic lose-lose.
- nerdsniper 1y ago
  ChatGPT, Gemini, and Claude all point me to a plethora of sources for most of my questions that I can click through and read. They're also pretty good at both basic and weird git issues for me. Not perfect, but pretty good. Also part of the workflow of using AI is accepting that your initial prompts might not get the right answer. It's important to scan the answer like you did and use intuition to know 'this isn't right', then try again. Just like we learned how to type in good search queries, we'll also learn how to write good prompts. Sands will shift frequently at first, with prompt strategies that worked well yesterday requiring a different strategy tomorrow, but eventually it will stabilize like search query strategies did.
avbanks 1y ago
This is exactly how I've been seeing it. If you're deeply knowledgable in a particular domain like lets say compiler optimization I'm unsure if LLM's will increase your capabilities (your ceiling), however, if you're working in a new domain LLMs are pretty good at helping you get oriented and thus raising the floor.
WealthVsSurvive 1y ago
AI is now most of Hackernews, so the internet is now talking ghosts.

370 points by jjfoooo4 1y ago

bitwize 1y ago

AI is a shovel capable of breaking through the bottom of the barrel.

manyaoman 1y ago

AI is a wall raiser.

spullara 1y ago

[flagged]

bugbuddy 1y ago
Imagine how useful it would be we could just add a button show our approval or disapproval of a piece of content without having to type true or false in the comment section. Let’s call it upvote or downvote button. /s
- crazygringo 1y ago
  I agree it wasn't a helpful comment. On the other hand, I don't know what this mythical downvote button for stories is you describe. I've certainly never seen it. Would be nice if HN actually had that.
  - falcor84 1y ago
    It's what "flag" is for: > Please don't complain that a submission is inappropriate. If a story is spam or off-topic, flag it. Don't feed egregious comments by replying; flag them instead. If you flag, please don't also comment that you did. https://news.ycombinator.com/newsguidelines.html https://news.ycombinator.com/newsguidelines.html
    - dns_snek 1y ago
      This article is neither spam nor off topic.
      - falcor84 1y ago
        I would agree, and have personally enjoyed the article. I just assumed that the person who wrote "false" might have considered it to be spam (perhaps in the broader sense), and if they did, flagging is considered to be the proper way of showing their disagreement.
    - crazygringo 1y ago
      No it's not. There are a lot of stories that aren't worthy of flagging, but they're just low-quality. And I've seen people abuse flagging because they treat it like downvoting. Flagging removes a story from the front page entirely, whereas ideally downvoting would simply deprioritize it, i.e. a bunch of downvotes would move it from #5 rank to #60 or something, not get rid of it entirely. I've definitely had to e-mail the mods a number of times to restore a flagged story that was entirely appropriate, but which a few users simply didn't like. It would be much better to have a downvote button, and reserve flagging for actual spam and inappropriate content.
      - spullara 1y ago
        i have seen a lot of speculation about my "false" comment on this story. i think the story is bullshit and AI 100% it raises the ceiling and doesn't help incompetent people that much. you see it over and over where incompetent people use AI and submit legal docs with hallucinations or have egregious security holes in their vibe coded projects. but i have seen highly skilled folks get month long projects done in a day with higher quality, more tests and more features than they would in the past. explaining all that didn't seem necessary since the whole thing is just not true.

amelius 1y ago

AI is an interpolator, not an extrapolator.

throe23486 1y ago
I read this as interloper. What's an extraloper?
- exasperaited 1y ago
  Opposite of "inter-" is "intra-". Intraloper, weirdly enough, is a word in use.
  - djeastm 1y ago
    So we have also have the word "extra", but oddly the word "exter" is left out. I'm exter mad about that.
  - jjk166 1y ago
    "inter-" means between, "intra-" means within, "extra-" means outside. "intra-" and "inter" aren't quite synonyms but they definitely aren't opposites of eachother.
    - exasperaited 1y ago
      Inter- implies relationships between entities, intra- implies relationships within entities. In any single sentence context they cannot refer to the same relationships, and that which they are not is precisely the domain of the other word: they are true antonyms.
      - jjk166 1y ago
        > and that which they are not is precisely the domain of the other word External relationships are a thing, which are in neither of those domains. An intramural activity is not the same thing as an intermural activity, but the overwhelming majority of activities which are not intramural activities are not intermural activities either, most are extramural activities.

lupire 1y ago

OP doesn't understand that almost everything is neither at the floor or the ceiling.

givemeethekeys 1y ago

AI is a floor destroyer not a ceiling destroyer. Hang on for dear life!! :P

bfigares 1y ago

AI raises everything - the ceiling is just being more productive. Productivity comes from adequacy and potency of tools. We got a hell of a strong tool in our hands, therefore, the more adequate the usage, the higher the leverage.

infecto 1y ago
Surprised to see this downvoted. It feels true to me. Sure there are definitely novel areas where folks might not benefit but I can see a future where this tool becomes helpful for the vast majority of roles.

andrenotgiant 1y ago

This tracks for other areas of AI I am more familiar with. Below average people can use AI to get average results.

itsoktocry 1y ago
That explains why people here are against it, because everyone is above average I guess.
- falcor84 1y ago
  I'm not against it. I wonder where in the distribution it puts me.
  - leptons 1y ago
    At the "Someone willing to waste their time with slop" end?
    - falcor84 1y ago
      Seeing that it gives me code that I then then use, then it's not a waste of my time.
      - leptons 1y ago
        A broken clock is right twice a day. If you're spending more time writing instructions for the AI, and then rewriting those instructions several times before you get usable code, then you're absolutely wasting your time. At least this is my experience with "AI". Even the fancy autocomplete portion of "AI" gets in my way more than it helps. Of course, YMMV, but I seriously doubt you're doing any better with "AI" than anyone else actually is, and a lot of people using it just don't realize all the time it's wasting, if they paid attention and added it all up.
pcrh 1y ago
This is in line with another quip about AI: You need to know more than the LLM in order to gain any benefit from it.

erlend_sh 1y ago

Only for the people already affluent enough to afford the ever-more expensive subscriptions. Those most in need of a floor-raising don’t have the disposable income to take a bet on AI.

intended 1y ago
Either you are the item being sold or you are paying for the service. Nothing is free, and I for one prefer a subscription model, if only as a change from the ad model. I am sure we will see the worst of all worlds, but for now, for this moment in history, subscription is better than ads. Let’s also never have ads in GenAi tools. The kind of invasive intent level influence these things can achieve, will make our current situation look like a paradise
- quirkot 1y ago
  I'd never buy anything as overt as an advertisement in an AI tool. I just want to buy influence. Just coincidentally use my product as the example. Just suggest my preferred technology when asked a few % more often than my competitors. I'd never want someone to observe me pulling the strings
- LtWorf 1y ago
  Normally even if you pay you're still the product anyway. See buying smartphones for example… you pay a lot but you're the product.
pdntspa 1y ago
It's very easy to sign up for an API account and pay per-call, or even nothing. Free offerings out there are great (Gemini, OpenRouter...) and a few are even suitable for agentic development.
- LtWorf 1y ago
  And how long until they raise the prices?

recroad 1y ago

AI isn't a pit. AI is a ladder.

anthk 1y ago
Yeah, like in Nethack, while being blind and stepping on a cockatrice.
layer8 1y ago
A ladder that doesn't reach the ceiling and sometimes ends up in imaginary universes.

billyp-rva 1y ago

Mixing this with a metaphor from earlier: giving a child a credit card is also a floor raiser.

manmal 1y ago

Since agents are good only at greenfield projects, the logical conclusion is that existing codebases have to be prepared such that new features are (opinionated) greenfield projects - let all the wiring dangle out of the wall so the intern just has to plug in the appliance. All the rest has to be done by humans, or the intern will rip open the wall to hang a picture.

PaulHoule 1y ago
Hogwash. If you can't figure out how to do something with project Y from npm try checking it out from Github with WebStorm and asking Junie how to do it -- often you get a good answer right away. If not you can ask questions that can help you understand the code base. Don't understand some data structure which is a maze of Map<String, Objects>(s) it will scan how it is used and give you draft documentation. Sure you can't point it to a Jira ticket and get a PR but you certainly can use it as a pair programmer. I wouldn't say it is much faster than working alone but I end up writing more tests and arguing with it over error handling means I do a better job in the end.
- falcor84 1y ago
  > Sure you can't point it to a Jira ticket and get a PR You absolutely can. This is exactly what SWE-Bench[0] measures, and I've been amazed at how quickly AIs have been climbing those ladders. I personally have been using Warp [1] a lot recently and in quite a lot of low-medium difficulty cases it can one-shot a decent PR. For most of my work I still find that I need to pair with it to get sufficiently good results (and that's why I still prefer it to something cloud-based like Codex [2], but otherwise it's quite good too), and I expect the situation to flip over the coming couple of years. [0] https://www.swebench.com/ https://www.swebench.com/ [1] https://www.warp.dev/ https://www.warp.dev/ [2] https://openai.com/index/introducing-codex/ https://openai.com/index/introducing-codex/
  - esafak 1y ago
    How does Warp compare to others you have tried?

BoredPositron 1y ago

AI is chairs.

furyofantares 1y ago
I feel like nobody remembers that facebook ad (Facebook is chairs), but it's seared into my own memory.
- anon35 1y ago
  https://www.youtube.com/watch?v=SSzoDPptYNA&t=53s https://www.youtube.com/watch?v=SSzoDPptYNA&t=53s

msgodel 1y ago

You'll find many people lack the willpower and confidence to even get on the floor though. If it weren't for that they'd already know a programming language and be selling something.

TimPC 1y ago

People should be worried because right now AI is on an exponential growth trajectory and no-one knows when it will level off into an s-curve. AI is starting to get close to good enough. If it becomes twice as good in seven months then what?

mattnewport 1y ago
What's the basis for your claim that it is on an exponential growth trajectory? That's not the way it feels to me as a fairly heavy user, it feels more like an asymptotic approach to expert human level performance where each new model gets a bit closer but is not yet reaching it, at least in areas where I am expert enough to judge. Improvements since the original ChatGPT don't feel exponential to me.
- samsartor 1y ago
  This also tracks with my experience. Of course, technical progress never looks smooth through the steep part of the s-curve, more a sequence of jagged stair-steps (each their own little s-curve in miniature). We might only be at the top of a stair. But my feeling is that we're exhausting the form-factor of LLMs. If something new and impressive comes along it'll be shaped different and fill a different niche.
nwienert 1y ago
Let's look: GPT-1 June 2018 GPT-2 February 2019 GPT-3 November 2021 GPT-4 March 2023 Claude tells me this is the rough improvement of each: GPT-1 to 2: 5-10x GPT-2 to 3: 10-20x GPT 3 to 4: 2-4x Now it's been 2.5 years since 4. Are you expecting 5 to be 2-4x better, or 10-20x better?
- esafak 1y ago
  How are you measuring this improvement factor? We have numerous benchmarks for LLMs and they are all saturating. We are rapidly approaching AGI by that measure, and headed towards ASI. They still won't be "human" but they will be able to do everything humans can, and more.

LeftHandPath 1y ago

There are some things that you still can't do with LLMs. For example, if you tried to learn chess by having the LLM play against you, you'd quickly find that it isn't able to track a series of moves for very long (usually 5-10 turns; the longest I've seen it last was 18) before it starts making illegal choices. It also generally accepts invalid moves from your side, so you'll never be corrected if you're wrong about how to use a certain piece. Because it can't actually model these complex problems, it really requires awareness from the user regarding what questions should and shouldn't be asked. An LLM can probably tell you how a knight moves, or how to respond to the London System. It probably can't play a full game of chess with you, and will virtually never be able to advise you on the best move given the state of the board. It probably can give you information about big companies that are well-covered in its training data. It probably can't give you good information about most sub-$1b public companies. But, if you ask, it will give a confident answer. They're a minefield for most people and use cases, because people aren't aware of how wrong they can be, and the errors take effort and knowledge to notice. It's like walking on a glacier and hoping your next step doesn't plunge through the snow and into a deep, hidden crevasse.

smiley1437 1y ago
> people aren't aware of how wrong they can be, and the errors take effort and knowledge to notice. I have friends who are highly educated professionals (PhDs, MDs) who just assume that AI\LLMs make no mistakes. They were shocked that it's possible for hallucinations to occur. I wonder if there's a halo effect where the perfect grammar, structure, and confidence of LLM output causes some users to assume expertise?
- bayindirh 1y ago
  Computers are always touted as deterministic machines. You can't argue with a compiler, or Excel's formula editor. AI, in all its glory, is seen as an extension of that. A deterministic thing which is meticulously crafted to provide an undisputed truth, and it can't make mistakes because computers are deterministic machines. The idea of LLMs being networks with weights plus some randomness is both a vague and too complicated abstraction for most people. Also, companies tend to say this part very quietly, so when people read the fine print, they get shocked.

tayo42 1y ago

I was thinking about this sentiment on my long car drive today. it feels like when you need to paint walls in your house. If you've never done it before you'll probably reach for tape to make sure you don't ruin the ceiling and floors. the tape is a tool for amateur wall painters to get decent results somewhat efficiently compared to if they didn't. If your an actual good wall painter, tape only slows you down. You'll go faster without the "help".

stillpointlab 1y ago

This mirrors insights from Andrew Ng's recent AI startup talk [1]. I recall he mentions in this video that the new advice they are giving to founders is to throw away prototypes when they pivot instead of building onto a core foundation. This is because of the effects described in the article. He also gives some provisional numbers (see the section "Rapid Prototyping and Engineering" and slides ~10:30) where he suggests prototype development sees a 10x boost compared to a 30-50% improvement for existing production codebases. This feels vaguely analogous to the switch from "pets" to "livestock" when the industry switched from VMs to containers. Except, the new view is that your codebase is more like livestock and less like a pet. If true (and no doubt this will be a contentious topic to programmers who are excellent "pet" owners) then there may be some advantage in this new coding agent world to getting in on the ground floor and adopting practices that make LLMs productive. 1. https://www.youtube.com/watch?v=RNJCfif1dPY https://www.youtube.com/watch?v=RNJCfif1dPY

falcor84 1y ago
Great point, but just mentioning (nitpicking?) that I never heard about machines/containers referred to as "livestock", but rather in my milieu it's always "pets" vs "cattle". I now wonder if it's a geographical thing.
- HPsquared 1y ago
  Boxen? (Oxen)
  - bayindirh 1y ago
    AFAIK, Boxen is a permutation of Boxes, not Oxen.
    - mananaysiempre 1y ago
      There seems to be a pattern of humorous plurals in English where by analogy with ox ~ oxen you get -x ~ -xen: boxen, Unixen, VAXen. Before you call this pattern silly, consider that the fairly normal plural “Unices” is by analogy with Latin plurals in -x = -c|s ~ -c|ēs, where I’ve expanded -x into -cs to make it clear that the Latin singular comprises a noun stem ending in -c- and a (nominative) singular ending -s, which does exist in Latin but is otherwise completely nonexistent in English. (This is extra funny for Unix < Unics < Multics.) Analogies are the order of the day in this language.

bluefirebrand 1y ago

AI is not a floor raiser It is a false confidence generator

burnt-resistor 1y ago
It seems most suitable as an autonomous political speech writer and used car salesman coach.

falcor84 1y ago

I agree with most of TFA but not this: > This means cheaters will plateau at whatever level the AI can provide From my experience, the skill of using AI effectively is of treating the AI with a "growth mindset" rather than a "fixed" one. What I do is that I roleplay as the AI's manager, giving it a task, and as long as I know enough to tell whether its output is "good enough", I can lend it some of my metagcognition via prompting to get it to continue working through obstacles until I'm happy with the result. There are diminishing returns of course, but I found that I can get significantly better quality output than what it gave me initially without having to learn the "how" of the skill myself (i.e. I'm still "cheating"), and only focusing my learning on the boundary of what is hard about the task. By doing this, I feel that over time I become a better manager in that domain, without having to spend the amount of effort to become a practitioner myself.

tailspin2019 1y ago
I wouldn’t classify what you’re doing as “cheating”!
righthand 1y ago
How do you know it’s significantly better quality if you don’t know any of the “how”? The quality increase seems relative to the garbage you start with. I guess as long as you impress yourself with the result it doesn’t matter if it’s not actually higher quality.
- razzmatazmania 1y ago
  I don't think "quality" has anything like a universal definition, and when people say that they probably mean an alignment with personal taste. Does it solve the problem? As long as it isn't prohibitively costly in terms of time or resources, then the rest is really just taste. As a user I have no interest whatsoever if your code is "idiomatic" or "modular" or "functional". In other industries "quality" usually means free of defects, but software is unique in that we just expect products to be defective. Your surgeon operates on the wrong knee? The board could revoke the license, and you are getting a windfall settlement. A bridge design fails? Someone is getting sued or even prosecuted. SharePoint gets breached? Well, that's just one of those things, I guess. I'm not really bothered that AI is peeing in the pool that has been a sewer as long as I can remember. At least the AI doesn't bill at an attorney's rate to write a mess that barely works.

fellowniusmonk 1y ago

The greatest use of LLMs is the ability to get accurate answers to queries in a normalized format without having to wade through UI distraction like ads and social media. It's the opposite of finding an answer on reddit, insta, tvtropes. I can't wait for the first distraction free OS that is a thinking and imagination helper and not a consumption device where I have to block urls on my router so my kids don't get sucked into a skinners box. I love being able to get answers from documentation and work questions without having to wade through some arbitrary UI bs a designer has implemented in adhoc fashion.

leptons 1y ago
I don't find the "AI" answers all that accurate, and in some cases they are bordering on a liability even if way down below all the "AI" slop it says "AI responses may include mistakes". >It's the opposite of finding an answer on reddit, insta, tvtropes. Yeah it really is because I can tell when someone doesn't know the topic well on reddit, or other forums, but usually someone does and the answer is there. Unfortunately the "AI" was trained on all of this, and the "AI" is just as likely to spit out the wrong answer as the correct one. That is not an improvement on anything. > wade through UI distraction like ads and social media Oh, so you think "AI" is going to be free and clear forever? Enjoy it while it lasts, because these "AI" companies are in way over their heads, they are bleeding money like their aorta is a fire hose, and there will be plenty of ads and social whatever coming to brighten your day soon enough. The free ride won't go on forever - think of it as a "loss leader" to get you hooked.
- margalabargala 1y ago
  I agree with the whole first half, but I disagree that LLM usage is doomed to ad-filled shittyness. AI companies may be hemmoraging money, but that's because their product costs so much to run; it's not like they don't have revenue. The thing that will bring profitability isn't ads, it will be innovations that let current-gen-quality LLMs run at a fraction of the electricity and power cost. Will some LLMs have ads? Sure, especially at a free tier. But I bet the option to pay $20/month for ad-free LLM usage will always be there.

gruez 1y ago

The blog post has a bunch of charts, which gives it a veneer of objectivity and rigor, but in reality it's just all vibes and conjecture. Meanwhile recent empirical studies actually point in the opposite direction, showing that AI use increases inequality, not decrease it. https://www.economist.com/content-assets/images/20250215_FNC938.png https://www.economist.com/content-assets/images/20250215_FNC... https://www.economist.com/finance-and-economics/2025/02/13/how-ai-will-divide-the-best-from-the-rest https://www.economist.com/finance-and-economics/2025/02/13/h...

Calavar 1y ago
The graphic has four studies that show increased inequality and six that show reduced inequality.
- gruez 1y ago
  Read my comment again. keyword here is "recent". The second link also expands on why it's relevant. It's best to read the whole article, but here's a paragraph that captures the argument: >The shift in recent economic research supports his observation. Although early studies suggested that lower performers could benefit simply by copying AI outputs, newer studies look at more complex tasks, such as scientific research, running a business and investing money. In these contexts, high performers benefit far more than their lower-performing peers. In some cases, less productive workers see no improvement, or even lose ground.
  - jjk166 1y ago
    All of the studies were done 2023-2024 and are not listed in order that they were conducted. The studies showing reduced equality all apply to uncommon tasks like material discovery and debate points, whereas the ones showing increased equality are broader and more commonly applicable, like writing, customer interaction, and coding.
    - deleted 1y ago
      [deleted]

verelo 1y ago

Oh man i love this take. It's how I've been selling what I do when I speak with a specific segment of my audience: "My goal isn't to make the best realtors better, it's to make the worst realtors acceptable". And my client is often the brokerage, they just want their agents to produce commissions so they make a cut. They know their top producers probably wont get much from what I offer, but we all see that their worst performers could easily double their business.

cropher 1y ago

Really liked this article. I wonder: the graphs treat learning with and without AI as two different paths. But obviously people can switch between learning methods or abandon one of them. Then again, I wonder how many people go from learning about a topic using LLMs to then leaving them behind to continue the old school way. I think the early spoils of LLM usage could poison your motivation to engage with the topic on your own later on.

serial_dev 1y ago
I learn about different subjects mixing traditional resources and AI. I can watch a video about the subject, when I want to go deeper, I go to LLMs, throw a bunch of questions at it, because thanks to the videos I now know what to ask. Then the AI responses tell me what I need to understand deeper, so I pick a book that addresses those subjects. Then as I read the book and I don’t understand something, or I have some questions that I want the answer for immediately, I consult ChatGPT (or any other tool I want to try). At different points in the journey, I find something I could build myself to deepen my understanding. I google open source implementations, read them, ask LLMs again, I watch summary videos, and work my way through the problem. LLMs serve as a “much better StackOverflow / Google”.
- bloomca 1y ago
  I use a similar approach. I tried to experiment going into a topic with no knowledge and it kinda fumbles, I highly recommend to have an overview. But once you know basics, LLMs are really good to deepen the knowledge, but using only them is quite challenging. But as a complementary tool I find them excellent.

precompute 1y ago

I'd argue that AI reduces the distance between the floor and the ceiling, only both the floor and ceiling move -- the floor moves up, the ceiling downwards. Just using AI makes the floor move up, while over-reliance on it (a very personal metric) pushes the ceiling downwards. Unlike the telephone (telephones excited a certain class of people into believing that world-wide enlightenment was on their doorstep), LLMs don't just reduce reliance on visual tells and mannerisms, they reduce reliance on thinking itself. And that's a very dangerous slope to go down on. What will happen to the next generation when their parents supply substandard socially-computed results of their mental work (aka language)? Culture will decay and societal norms will veer towards anti-civilizational trends. And that's exactly what we're witnessing these days. The things that were commonplace are now rare and sometimes mythic. Everyone has the same number of hours and days and years. Some people master some difficult, arcane field while others while it away in front of the television. LLMs make it easier for the television-watchers to experience "entertainment nirvana" while enticing the smart, hard-workers to give up their toil and engage "just a little" rest, which due to the insidious nature of AI-based entertainment, meshes more readily with their more receptive minds.

guywithahat 1y ago

Wouldn't it be both by this definition? It raises the bar for people who maybe have a lower IQ ("mastery"), but people who can us AI can then do more than ever before, raising the ceiling as well.

kruffalon 1y ago
Wouldn't "more" in this house metaphor be like expanding the floor rather than raising the ceiling?

sabaimran 1y ago

In things that I am comparatively good at (e.g., coding), I can see that it helps 'raise the ceiling' as a result of allowing me to complete more of the low level tasks more effectively. But it is true as well that it hasn't raised my personal bar in capability, as far as I can measure. When it comes to things I am not good at at, it has given me the illusion of getting 'up to speed' faster. Perhaps that's a personal ceiling raise? I think a lot of these upskilling utilities will come down to delivery format. If you use a chat that gives you answers, don't expect to get better at that topic. If you use a tool that forces you to come up with answers yourself and get personalized validation, you might find yourself leveling up.

spartanatreyu 1y ago
> When it comes to things I am not good at at, it has given me the illusion of getting 'up to speed' faster. Perhaps that's a personal ceiling raise? Disagree. It's only the illusion of a personal ceiling raise. --- Example 1: Alice has a simple basic text only blog. She wants to update the styles on his website, but wants to keep his previous posts. She does research to learn how to update a page's styles to something more "modern". She updates the homepage, post page, about page. She doesn't know how to update the login page without breaking it because it uses different elements she hasn't seen before. She does research to learn what the new form elements and on the way sees recommendations on how to build login systems. She builds some test pages to learn how to restyle forms and while she's at it, also learns how to build login systems. She redesigns her login page. Alice believes she has raised the ceiling what she can accomplish. Alice is correct. --- Example 2: Bob has a simple basic text only blog. He wants to update the styles on his website, but wants to keep his previous posts. He asks the LLM to help him update styles to something more "modern". He updates the homepage, post page, about page, and login page. The login page doesn't work anymore. Bob asks the LLM to fix it and after some back and forth it works again. Bob believes she has raised the ceiling what he can accomplish. Bob is incorrect. He has not increased his own knowledge or abilities. A week later his posts are gone. --- There are only a few differences between both examples: 1. Alice does not use LLMs, but Bob does. 2. Alice knows how to redesign pages, but Bob does not. 3. Alice knows how login systems work, but Bob does not. Bob simply asked the LLM to redesign the login page, and it did. When the page broke, he checked that he was definitely using the right username and password but it still wasn't working. He asked the LLM to change the login page to always work with his username and password. The LLM produced a login form that now always accepted a hard coded username and password. The hardcoded check was taking place on the client where the username and password were now publicly viewable. Bob didn't ask the LLM to make the form secure, he didn't even know that he had to ask. He didn't know what any of the footguns to avoid were because he didn't even know there were any footguns to avoid in the first place. Both Alice and Bob started from the same place. They both lacked knowledge on how login systems should be built. That knowledge was known because it is documented somewhere, but it was unknown to them. It is a "known unknown". When Alice learned how to style form elements, she also read links on how forms work which lead her to links on how login systems work. That knowledge for her went from an unknown known to a "known known" (knowledge that is known, that she now also knows). When Bob asked the LLM to redesign his login page, at no point in time does the knowledge of how login systems work become a "known known" for him. And a week later some bored kid finds the page, right clicks on the form, clicks inspect and sees a username and password to log in with.

resters 1y ago

AI will be both a floor and a ceiling raiser, since there is a practical limit to how many domains one person or team can be expert in, and AI does/will have very strong levels of expertise/competency across a large number of domains and will thus offer significant level-ups in areas where cross-domain synthesis is crucial or where the limits of human working memory and pattern recognition make cross-domain synthesis unlikely to occur. AI also enables much more efficient early stage idea validation, the point at which ideas/projects are the least anchored in established theory/technique. Thus AI will be a great aid in idea generation and early stage refinement, which is where most novel approaches stall or sit on a shelf as a hobby project because the progenitor doesn't have enough spare time to work through it.

righthand 1y ago

It’s definitely about wage stagnation.

burnt-resistor 1y ago
Wage suppression. The capital ownership class knows exactly how to weaponize the hype as an excuse now. It's also curious how software engineers working on it are cheerfully building their potential future replacements and long-term insecurity.

buffzebra 1y ago

Only the first two mastery-time graphs make sense.

resters 1y ago

AI is going to cause a regression to the most anodyne output across many industries. As humans who had to develop analytical skills, writing skills, etc., we struggle to imagine the undeveloped brains of those who come of age in the zero-intellectual-gravity world of AI. OpenAI's study mode is at best a fig leaf. edit: this comment was posted tongue-in-cheek after my comment reflecting my actual opinion was downvoted with no rebuttals: https://news.ycombinator.com/item?id=44749957 https://news.ycombinator.com/item?id=44749957

elcritch 1y ago
I would say the modern digital world itself has already had the bigger impact on human thinking, at least at work. It seems with computers we often think and reason far less than without. Everything required thought previously, now we can just copy and paste out word docs for everything. PowerPoints are how key decisions are communicated in most professional settings. Before modern computers and especially the internet we also had more time for deep thinking and reasoning. The sublimity of deep thought in older books amazes me and it feels like modern authors are just slightly less deep on average. So then LLMs are in my view an incremental change rather than a stepwise change with respect to its effects on human cognitive. In some ways LLMs allow us to return a bit to more humanistic deep thinking. Instead of spending hours looking up minutia on Google, StackOverflow, etc now we can ask our favorite LLM instead. It gives us responses with far less noise. Unlike with textbooks we can have dialogues and have it take different perspectives. Whereas textbooks only gave you that authors perspective. Of course, it’s up to individuals to use it well and as a tool to sharpen thinking rather than replace it.

michaelhoney 1y ago

I think all of this is true, but the shape of the chart changes as AI gets better. Think of how a similar chart for chess/go/starcraft-playing proficiency has changed over the years. There will come a time when the hardest work is being done by AI. Will that be three years from now or thirty? We don't know yet, but it will come.

dcchambers 1y ago

I mean it makes sense that if the AI is trained on human-created things it can never actually do better than that. Can't bust through the ceiling of what it was trained on. And at the same time, it AI gives that power to people that just aren't very smart or good at something.

m3kw9 1y ago

At the very least

Madmallard 1y ago

I guess the AI glazing has infiltrated everywhere

godelski 1y ago

I think a good way to see it is "AI is good for prototyping. AI is not good for engineering" To clarify, I mean that the AI tools can help you get things done really fast but they lack both breadth and depth. You can move fast with them to generate proofs of concept (even around subproblems to large problems), but without breadth they lack the big picture context and without depth they lack the insights that any greybeard (master) has. On the other hand, the "engineering" side is so much more than "things work". It is about everything working in the right way, handling edge cases, being cognizant of context, creating failure modes, and all these other things. You could be the best programmer in the world, but that wouldn't mean you're even a good engineer (in real world these are coupled as skills learned simultaneously. You could be a perfect leetcoder and not helpful on an actual team, but these skills correlate). The thing is, there will never be a magic button that a manager can press to engineer a product. The thing is, for a graybeard most of the time isn't spent around implementation, but design. The thing is, to get to mastery you need experience, and that experience requires understanding of nuanced things. Things that are non-obvious. There may be a magic button that allows an engineer to generate all the code for codebase, but that doesn't replace engineers. (I think this is also a problem in how we've been designing AI code generators. It's as if they're designed for management to magically generate features. The same thing they wish they could do with their engineers. But I think the better tool would be to focus on making a code generator that would generate based on an engineer's description. I think Dijkstra's comments apply today just as much as they did then[0] [0] On the foolishness of "natural language programming" https://www.cs.utexas.edu/~EWD/transcriptions/EWD06xx/EWD667.html https://www.cs.utexas.edu/~EWD/transcriptions/EWD06xx/EWD667...

per1Peteia 1y ago
I was reading some stuff by Michael A. Jackson (Problem Frames Approach) and T.S.E Maibaum (Mathematical Foundations on Software Engineering) because I also had the impression that too much talk around LLM-assisted programming focuses on program text and annotations / documentation. Thinkers like Donald Schön thought about tacit knowledge-in-action and approached this with design philosophy. when looking at LLM-assisted programming, I call this shaded context. as you say, software engineering is not only constructing program texts, its not even only applied math or overly scientific. at least that is my stance. I suspect AI code editors have lots of said tacit knowledge baked in (via the black box itself or its engineers) but we would be better off thinking about this explicitly.

BrenBarn 1y ago

In one sense it's a floor-lowerer, since it lowers the floor on how clueless you can be and still produce something loosely describably as software.

atlgator 1y ago

I'm not sure this is my experience so far. What I'm noticing is that my awesome developers have embraced AI as an accelerator, particularly for research and system design, small targeted coding activities with guardrails. My below average developers are having difficulty integrating AI at all in their workflow. If this trend continues the chasm between great and mediocre devs will widen dramatically.

PeterStuer 1y ago

Most non-trivial expertise topics are not one-dimensional. You might be at the "ceiling" in some particular sub-niche, while still on the floor on other aspects of the topic. So even if you follow the artcles premise (I do not), it still can potentially 'raise' you wherever you were. Key seems to be wether you have enough expertise to evaluate or test the outputs. Some others have refered to this as having a good sense of the "known/unknown" matrix for the domain. The AI will be most helpful for you in the known-unknown / unknown-known axis, not so much in the known-known / unknown-unknown parts. The latter unfortunatly is were you see the most derailed use of the tech.

ygritte 1y ago

At least the last coding-with-AI chart is still too optimistic, I think. It doesn't reflect how AI coding tools are making developers less productive (instead of more) in non-trivial projects.

rnaarten 1y ago

The blog still assumes that AI does not affect Mastery. I think it does. All the AI junk like Agents in Service centers that you need to outplay in order to get in touch with a human, us as consumers are accepting this new status quo. We will accept products that sometimes can do crazy stuff because of hallucinations. Why? Ultimate capitalism consumerism sheepism, some other ism. So AI (and whether it is correlarion or causation, i dont know) also corresponds with lower level of Mastery

conartist6 1y ago

The learning-with-AI curve should cross back under the learning-without-AI curve at towards the higher end even without "cheating". The very highest levels of mastery can only come from slow, careful, self-directed learning that someone in a hurry to speedrun the process isn't focusing on.

careful_ai 1y ago

[dead]

mensetmanusman 1y ago

The second derivative of floor raiser is ceiling raising.

nunez 1y ago

So speaking of "mastery": I wanted to know how to clone a single folder in a Git repository. Having done this before, I knew that there was some incantation I needed to make to the git CLI to do it, but I couldn't remember what it was. I'm very anti-AI for a number of reasons, but I've been trying to use it here and there to give it the benefit of the doubt and avoid becoming a _complete_ dinosaur. (I was very anti-vim ages ago when I learned emacs; I spent two weeks with vim and never looked back. I apply this philosophy to almost everything as a result.) I asked Qwen3-235B (reasoning) via Kagi Assistant how I could do this. It gave me a long block of text back that told me to do the thing I didn't want it to do: mkdir a directory, clone into it, move the directory I wanted into the root of the directory, delete everything else. When I asked it if it was possible to do this without creating the directory, it, incorrectly, told me that it was not. It used RAG-retrieved content in its chain of thought, for what that's worth. It took me only 30 seconds or so to find the answer I wanted on StackOverflow. It was the second most popular answer in the thread. (git clone --filter=tree: --depth=0, then git sparse-checkout set --no-cone $FOLDER, found here: https://stackoverflow.com/a/52269934 https://stackoverflow.com/a/52269934) I nudged the Assistant a smidge more by asking it if there was a subcommand I could use instead. It, then, suggested "sparse-checkout init", which, according to the man page for this subcommand, is deprecated in favor of "set". (I went to the man page to understand what the "cone" method was and stumbled on that tidbit.) THIS is the thing that disappoints me so much about LLMs being heralded as the next generation of search. Search engines give you many, many sources to guide you to the correct answer if you're willing to do the work. LLM services tell you what the "answer" is, even if it's wrong. You get potential misinformation back while also turning your brain off and learning less; a classic lose-lose.

nerdsniper 1y ago
ChatGPT, Gemini, and Claude all point me to a plethora of sources for most of my questions that I can click through and read. They're also pretty good at both basic and weird git issues for me. Not perfect, but pretty good. Also part of the workflow of using AI is accepting that your initial prompts might not get the right answer. It's important to scan the answer like you did and use intuition to know 'this isn't right', then try again. Just like we learned how to type in good search queries, we'll also learn how to write good prompts. Sands will shift frequently at first, with prompt strategies that worked well yesterday requiring a different strategy tomorrow, but eventually it will stabilize like search query strategies did.

avbanks 1y ago

This is exactly how I've been seeing it. If you're deeply knowledgable in a particular domain like lets say compiler optimization I'm unsure if LLM's will increase your capabilities (your ceiling), however, if you're working in a new domain LLMs are pretty good at helping you get oriented and thus raising the floor.

WealthVsSurvive 1y ago

AI is now most of Hackernews, so the internet is now talking ghosts.