7 ms·

What my dad taught me about AI coding in the 90s

147 points by askmike 25d ago

simonw 19d ago
I'm not completely convinced by this comparison between blind chess and prompting LLMs. In blind chess you get deterministic information about the state of the board: each mental update to your board model can be precise, and you have the full state at every point in time. LLMs are notoriously non-deterministic, and even at temperature zero you still can't predict exactly where the weights will take you next. I suppose you can get closer to deterministic if you adopt a prompting style where you almost dictate every line of code, but at that point the coding agent is more of a typing assistant. The productivity benefits of coding agents unlock themselves when you figure out how to turn short prompts - "add tests that exercise the registration form and check the happy path and all failure states" - into larger changes. If you're completely blind to the results of those you're going to end up with a system you don't 100% understand very quickly. In blind chess terms you'll no longer know the positions of every piece on the board.
- NameError 19d ago
  I agree with your take, particularly because of this line in the article: | the skills that define a strong blindfold chess player are the same as those of a programmer who can thrive behind a Claude Code terminal whilst not reading nor writing any code. If you're actually not reviewing the outputs, you're just getting a fuzzy description of the state of the chessboard. But I (and everyone I work with) use Claude Code in a workflow where I -do- review the outputs, or at least I make an honest effort to try. Rather than blindfolded, I think bullet (1-minute) chess is a fairly good analogy for this: you have all the info you need to keep your mental model up to date with reality, but the pace of change is too fast to do a good job unless you have a lot of preexisting chess expertise.
  - danielovichdk 19d ago
    You learn a lot more by reading code than writing it. So reading the output i believe is an immensely big gift by an LLM, because if you actually take note - and of course know your skills - then ot becomes such a great pal to work with. I like reading what the LMM gives me, not always, but a lot of times.
    - throwawee 19d ago
      > You learn a lot more by reading code than writing it. Really? In my experience it's been the opposite. It's like how you can learn more about art by trying to recreate it than just looking.
      - DoctorOetker 19d ago
        a lot of people get stuck, or code up a naive brute force algorithm and call it a day, nothing intrinsically forces a coder that refuses to look at the work of others to write better code.
    - lelanthran 19d ago
      > You learn a lot more by reading code than writing it. "You learn a lot more by reading trigonometry than by doing problems" See how ridiculous that sounds?
      - DoctorOetker 19d ago
        I can find a kernel of truth in both statements: As long as the literature contains insights a reader isn't aware about, reading the literature is low-hanging fruit compared to having to derive all the things yourself. As soon as the literature no longer contains insights, it becomes more productive to explore mathematics oneself by trial and error. Organized education will model this on a topic by topic basis: during class you're handed the more valuable insights on a silver platter, during an exam you are prevented from looking at your textbook. Every time you read a chapter and do the exercises it's a small simulacrum of catching low hanging fruit followed by making sure you can derive similar statements with trial and error for fixing any gaps. The trial and error while you do problems does improve your intuition, but only trial and error is like having every student redevelop the frontier starting from antiquity.
      - bwfan123 19d ago
        > See how ridiculous that sounds? For most of us, writing code is the way to carve out intuition into an artifact. But, I have noticed some people are able to read deeply - and by that I mean, reverse the code to understand the intuition that brought it to life. This is a rare skill and I dont have it, but some do. Not just for code, but also for any book - fiction or non-fiction - some are able to deconstruct the scenarios much better than others, and in that sense understand what they read.
- vunderba 19d ago
  IMHO the thrust of the article feels a bit forced, but LLM = Blindfold chess is not what the author is saying: > Thus in many ways programming with AI is the opposite of blindfold chess: you don't have to pay attention every turn, you don't have to remember what the important pieces are, the details of the tactical relationships (such as code interfaces and APIs).
  - relativeadv 19d ago
    That sentence was awkward. Maybe even a typo? The following sentences to the one you just quoted ignores that and proceeds to argue FOR blindfolded chess being like programming with LLMs. The article itself takes several paragraphs to get to the argument it wants to make and then ends having only argued for a few more sentences. No real evidence is provided either.
    - vunderba 19d ago
      Well no, it argues that the SKILLS for playing blindfold chess are similar to people who use LLMs to develop code - not that blindfold chess = vibe coding. And then earlier in the article defines said skills as having a sense of high-level relationships (chunking, positioning, etc) over the board rather than a photographic memory of the board. But as I said, the whole article feels very fluffy anyway.
- trollbridge 19d ago
  LLMs are notoriously non-deterministic, and even at temperature zero you still can't predict exactly where the weights will take you next. An LLM can be made to be completely deterministic. I use them in this mode so I can reproduce test cases. Of course it requires complete control over the model, etc. but this myth that a computer program is non-deterministic needs to end. You can 100% predict where the weights “will take you” given a set of inputs.
  - Folcon 19d ago
    > You can 100% predict where the weights “will take you” given a set of inputs. Do you mean reproduce? Sorry it's just if you are saying what your statement implying then either the model is very simple, or you've figured out something incredible
    - trollbridge 19d ago
      Sure. Take the inputs and run it through the model. You now have the output which will be perfectly reproduced with the same inputs.
  - techpression 19d ago
    You should publish, likely a Nobel price or Turing award waiting, and generational wealth at some tech giant.
  - simonw 19d ago
    By "can't predict exactly where the weights will take you next" I meant with your brain. The blind chess analogy suggests you can predict, using your own thought process, the exact output of a prompt.
    - trollbridge 19d ago
      I could use my brain to run a set weights, given enough time (on the order of millions of years).
  - shakna 19d ago
- andai 19d ago
  >you're going to end up with a system you don't 100% understand very quickly This has been my experience with all software projects. Even if I wrote all the code, my understanding of how everything works and fits together decays. ( See the Forgetting Curves https://en.wikipedia.org/wiki/Hermann_Ebbinghaus https://en.wikipedia.org/wiki/Hermann_Ebbinghaus )
  - simonw 19d ago
    Yeah, that's a fair point. I have plenty of older projects where I no longer understand how they work despite having written the code myself. I guess the key thing is that you need to be able to demonstrate to yourself that you understand the code at least once, because that means you should be able to revise how it works in the future. You also can't evaluate if a solution is fit for purpose if you don't understand it.
    - thec0d3 19d ago
      You don't buy the article's position but have forgotten a lot and not known a lot; so no need to care about your opinion I guess This is my beef with modern software engineers; complete detachment from physical reality where entropy is eroding structure (memory, generational churn). Code is just a euphemism for a desired electrical state. No need to dump biz contexts in code. Just make a game engine that efficiently handles geometry on screen and label the presentation layer. All ya'll are doing is recreating front end rendering technology, forgetting in time and recreating it in new semantics. It's absolutely fucking asinine. I look forward to models in chips and a tiny universal code base coupled to the machine. This whole allowing a bunch of unelected rhetoricians tell myself and other hardware engineers we need them to use our property is exhausting. It's rhetorical nonsense that goes in these broad loops recreating old work. Time to move on from what titillated you all as children. Or you will just end up entitled Boomers. Writing code like its 1970s is not high tech. It's old low tech
      - names_are_hard 18d ago
        This is either incredibly advanced, genius-level insight into the future of software engineering, or absolutely nonsensical gibberish. I'm not smart enough to tell which, I suppose we'll find out.
- deleted 19d ago
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dumbfounder 19d ago
Meh. Chess exists to entertain the players. Coding exists to solve problems. I see way too often the programmers think it’s all about the coder and the code. Solve the problem. Don’t write code at all to do that if you can (AI generated or otherwise).
- Supermancho 19d ago
  Once you get past trivial problems, the issue is not just "solving the problem" but proving the solution "solves the problem". This is the strongest argument as to why AI should only be used as small solvers (at this point).
- andai 19d ago
  Yeah, it's about incentives. Software development is about solving business problems, but sometimes the solution is "use this thing that already exists instead of paying me to build it." Similarly, the incentive is to design it so you will need to spend 10 years working on it, instead of 10 hours.
tikimcfee 19d ago
I really like this idea, because I think people forgetting that when you are writing code there exist a time T greater than zero, where you're not actually writing code and you're doing this thing called "thinking", ha ha. I find that there's a lot of times where I'm sitting staring at the screen and the lines of text sort of blur, and I'm in my head thinking about the connection of everything and not really worried about the actual implementation and how bites are moving, but wondering about the structure and the nature of the actual flow of the code. There's a wonderful XKCD about this, where a person sitting on a computer has this very beautiful stack of thoughts and clouds about what's being written, and then someone walks up to them and says something, and the entire cloud pops. If I understand this article, I think that's exactly a reasonable analogy to it. There is something that happens in the mind, and perhaps a neural weights, where the non-execution is where creativity and problem solving happening by mapping to the higher level concepts and stitching them together without having to specifically worry about the line level details. They still crop up, and implementation will probably always be king, But I do think I agree with this entirely!
yipinwong 19d ago
Analogies work at an abstraction, and gotta take the chess analogy at its face value, as deeper people go into what's different between the chess and real life (deterministic vs non-deministic), one is not getting the lesson the author is presenting. Remember, analogy is not territory. Every analogies fail at some point
lordnacho 19d ago
I think I agree. I guess I don't know enough about chess to be sure, but the idea seems to be that although to novices a blindfolded player must reconstruct the board in his mind, that is not actually what is done by the expert. That is something I can agree with, having spent a heck of a long time coding in the trading domain. I've managed to vibe code a trading system. It's a hobby project directed on my phone on my commute, but it does do all the things I find important about trading systems. I can connect to external exchanges and see that I have sent valid orders, I get fills, and I can see debug logs of the timestamps. It doesn't allocate memory on the hot path, cores can be pinned, and so on. There are benchmarks that say how fast the code is parsing messages. It works. So I've somehow built a thing that I've barely examined in the traditional sense, which nonetheless satisfies certain business needs for this hobby project. How could that be? If you transported me back two years, I would know exactly where to make whatever changes you desired. I had the IDE open all the time, and I knew where things were. Now, I don't even know what the internal structure is like, I just know whether consideration has been made for some aspect of the system. And I think this is what seems so baffling to a lot of people. How are software developers getting such different experiences with LLMs? Some people genuinely are producing things with incredible pace, while others find the AI just produces slop for them. Some people are ready for the blindfold, but many are not. It's incredibly frustrating, especially if you are reasonably advanced but not yet at that overview stage.
- deleted 19d ago
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mikeaskew4 19d ago
My dad just had a computer around and looked the other way when I spent all night on it. And I learned chess on my own. This may not be the argument Mike makes here, I have always felt that seeing the board and not knowing what it means is more valuable than knowing everything about it without seeing it. If you’re drowning, who do you want to save you, the lifeguard who can’t read or the author of the book on water lifesaving techniques who can’t swim?
yellow_lead 19d ago
Is there anything new in this article? Yes, experts use AI better than non-experts for tasks in their domain. See LLMs reward expertise [1] and Terrance Taos conversation with LLM [2]. [1] https://www.seangoedecke.com/llms-reward-expertise/ https://www.seangoedecke.com/llms-reward-expertise/ [2] https://chatgpt.com/share/6a5fdc7a-d6f8-83e8-bbea-8deb42cfed56 https://chatgpt.com/share/6a5fdc7a-d6f8-83e8-bbea-8deb42cfed...
- a2ff6eeb0 19d ago
  I think the need for expertise is also going away. For example, when Claude made progress on the Riemann conjecture, > Jarred's input was mostly limited to sending Claude messages of encouragement (mostly variants of “keep going” or “believe in yourself”).2 This seems to have helped Claude overcome some initial skepticism that it could make meaningful progress. https://www.anthropic.com/research/riemann-zeta https://www.anthropic.com/research/riemann-zeta The full transcript is here: https://www-cdn.anthropic.com/8a0d1add3c637b858a9a181e98c40e9548c3f44f.pdf https://www-cdn.anthropic.com/8a0d1add3c637b858a9a181e98c40e... We're on the border of fully outsourcing expertise.
  - yellow_lead 19d ago
    > Two mathematicians at Anthropic studied and validated Claude’s paper, and produced an informal note for experts stating Claude’s proof concisely. No, experts are still needed
    - a2ff6eeb0 19d ago
      Yes, that's why we're on the border: AI is doing its thing without us, but we're not yet confident enough to let the AI do its thing without checking. You may notice that humans only checked the work and explained. You may also see that that the person prompting the AI, Jared of bun.js fame, is not a noted expert in mathematics.
syou1024 19d ago
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qbane 19d ago
I do not think the metaphor can go very far. Have blindfolded chess become the "productivity trend" that every one should learn it to enjoy chess? Have normal chess players been replaced because skilled players can do blindfolded?
- deleted 19d ago
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a2ff6eeb0 19d ago
This makes no sense. The skills needed for AI coding are the same skills needed to hire Gary Kasparov to play chess. Tell them where the game is and stand back as they play.
F7F7F7 19d ago
This article reads like it was written by prompting AI for connections between two loosely connected things.
- brazukadev 19d ago
  No, this article does not look like it was written by prompting AI just because you didn't like it.
TZubiri 19d ago
Au contraire, playing blindfold is removing a tool, depending on nothing but your mind. Vibe coding is the opposite, not just depending on the chessboard, but depending on a couple of Gflops to even think. Blindfolded programming would be the programming we do in the shower
_diyar 19d ago
The analogy can be dragged one step further: once the engine is good enough, it’s functionally impractical for a human to play.
- dimitarbogdanov 19d ago
  I disagree. A chess engine has a very well defined goal and is working its patterns to reach that goal. In software development, except in a minority of cases, the goal is being set by non-technical people, who have no clue how the resulting system should end up, only what it should look like to a user. I think a well-versed programmer can give the AI direct instructions on how to implement something, and just let the LLM write the code to implement/refactor the infrastructure behind the feature they're developing. For me the plan mode of Claude Code is (anecdote incoming) much faster(TM) and better(TM) if I give it concrete instructions - then it writes the plan, asks questions - and then implements it. Very little complaints after that (I usually don't let Claude do any sort of visual QA)
dzonga 19d ago
it's a Sunday - I don't have time to put things into buckets. there's coding - writing code to do something could be a game, utility to move files around. what have you. inherently the nature is a closed domain. AI is perfect here - the impact if something goes wrong is close to 0 or null. then there's software engineering - which is both an art & science. u r dealing with rules of thumb. nothing is ever coded / written down. but a feel to whether something feels right or not. the domain is unbounded. the impact of something going wrong is catastrophic in all dimensions. coding is a delivery mechanism for software engineering. but not the actual work. using A.I here is useless. but we keep having these pieces - I guess that's just shallow the industry is.
mistrial9 19d ago
William E. "Bill" Bates in Berkeley coded an entire "virtual cat" demo in the late-1990s on the MacOS using neural nets and learning. source: eye-witness
paidx 19d ago
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lowbloodsugar 19d ago
I use AI every day and have unlimited budget. I will certainly not trust it to write safe, system level code for our systems. You absolutely do need to be playing blindfold chess and you can’t do that if the other actor doesn’t tell you the moves it made. Using LLMs as described here is essentially what vibe coding is all about. To use this chess analogy, the model says “checkmate!” and you just believe it because you never heard or looked at the moves it claimed to have made.
cryptolobster 19d ago
[flagged]
jpollock 18d ago
If you can't look at the code, you need to trust interfaces to specify (and constrain) the implementation. The implementation needs to implement the entire interface and can't do anything not in the interface. Otherwise, you're going to get bit by the Law of Leaky Abstractions. The number of times I've been bit by systems not adhering to interfaces? Yeah, that's pretty frequent. For example (from personal experience), the interface allows for race conditions, it's obvious they can happen (distributed systems), but the implementation didn't allow them, resulting in fun times.
sshine 18d ago
> if a seasoned programmer sits behind Claude Code, the quality output will likely be higher than if a non technical person does it Anecdotal: I recently rewrote a service in Rust for a much needed 100x performance boost (largely due to architectural changes, somewhat due to better runtime). My colleague who now maintains the app is not a Rust developer and knows little about threads and tokio. Debugging a problem, he said he’d reach the context window before pinning the problem. I never have that problem and effortlessly find problems in the first 100k tokens without trying. The difference must be in the wording that initially guides the agent.

147 points by askmike 25d ago

I'm not completely convinced by this comparison between blind chess and prompting LLMs. In blind chess you get deterministic information about the state of the board: each mental update to your board model can be precise, and you have the full state at every point in time. LLMs are notoriously non-deterministic, and even at temperature zero you still can't predict exactly where the weights will take you next. I suppose you can get closer to deterministic if you adopt a prompting style where you almost dictate every line of code, but at that point the coding agent is more of a typing assistant. The productivity benefits of coding agents unlock themselves when you figure out how to turn short prompts - "add tests that exercise the registration form and check the happy path and all failure states" - into larger changes. If you're completely blind to the results of those you're going to end up with a system you don't 100% understand very quickly. In blind chess terms you'll no longer know the positions of every piece on the board.

NameError 19d ago
I agree with your take, particularly because of this line in the article: | the skills that define a strong blindfold chess player are the same as those of a programmer who can thrive behind a Claude Code terminal whilst not reading nor writing any code. If you're actually not reviewing the outputs, you're just getting a fuzzy description of the state of the chessboard. But I (and everyone I work with) use Claude Code in a workflow where I -do- review the outputs, or at least I make an honest effort to try. Rather than blindfolded, I think bullet (1-minute) chess is a fairly good analogy for this: you have all the info you need to keep your mental model up to date with reality, but the pace of change is too fast to do a good job unless you have a lot of preexisting chess expertise.
- danielovichdk 19d ago
  You learn a lot more by reading code than writing it. So reading the output i believe is an immensely big gift by an LLM, because if you actually take note - and of course know your skills - then ot becomes such a great pal to work with. I like reading what the LMM gives me, not always, but a lot of times.
  - throwawee 19d ago
    > You learn a lot more by reading code than writing it. Really? In my experience it's been the opposite. It's like how you can learn more about art by trying to recreate it than just looking.
    - DoctorOetker 19d ago
      a lot of people get stuck, or code up a naive brute force algorithm and call it a day, nothing intrinsically forces a coder that refuses to look at the work of others to write better code.
  - lelanthran 19d ago
    > You learn a lot more by reading code than writing it. "You learn a lot more by reading trigonometry than by doing problems" See how ridiculous that sounds?
    - DoctorOetker 19d ago
      I can find a kernel of truth in both statements: As long as the literature contains insights a reader isn't aware about, reading the literature is low-hanging fruit compared to having to derive all the things yourself. As soon as the literature no longer contains insights, it becomes more productive to explore mathematics oneself by trial and error. Organized education will model this on a topic by topic basis: during class you're handed the more valuable insights on a silver platter, during an exam you are prevented from looking at your textbook. Every time you read a chapter and do the exercises it's a small simulacrum of catching low hanging fruit followed by making sure you can derive similar statements with trial and error for fixing any gaps. The trial and error while you do problems does improve your intuition, but only trial and error is like having every student redevelop the frontier starting from antiquity.
    - bwfan123 19d ago
      > See how ridiculous that sounds? For most of us, writing code is the way to carve out intuition into an artifact. But, I have noticed some people are able to read deeply - and by that I mean, reverse the code to understand the intuition that brought it to life. This is a rare skill and I dont have it, but some do. Not just for code, but also for any book - fiction or non-fiction - some are able to deconstruct the scenarios much better than others, and in that sense understand what they read.
vunderba 19d ago
IMHO the thrust of the article feels a bit forced, but LLM = Blindfold chess is not what the author is saying: > Thus in many ways programming with AI is the opposite of blindfold chess: you don't have to pay attention every turn, you don't have to remember what the important pieces are, the details of the tactical relationships (such as code interfaces and APIs).
- relativeadv 19d ago
  That sentence was awkward. Maybe even a typo? The following sentences to the one you just quoted ignores that and proceeds to argue FOR blindfolded chess being like programming with LLMs. The article itself takes several paragraphs to get to the argument it wants to make and then ends having only argued for a few more sentences. No real evidence is provided either.
  - vunderba 19d ago
    Well no, it argues that the SKILLS for playing blindfold chess are similar to people who use LLMs to develop code - not that blindfold chess = vibe coding. And then earlier in the article defines said skills as having a sense of high-level relationships (chunking, positioning, etc) over the board rather than a photographic memory of the board. But as I said, the whole article feels very fluffy anyway.
trollbridge 19d ago
LLMs are notoriously non-deterministic, and even at temperature zero you still can't predict exactly where the weights will take you next. An LLM can be made to be completely deterministic. I use them in this mode so I can reproduce test cases. Of course it requires complete control over the model, etc. but this myth that a computer program is non-deterministic needs to end. You can 100% predict where the weights “will take you” given a set of inputs.
- Folcon 19d ago
  > You can 100% predict where the weights “will take you” given a set of inputs. Do you mean reproduce? Sorry it's just if you are saying what your statement implying then either the model is very simple, or you've figured out something incredible
  - trollbridge 19d ago
    Sure. Take the inputs and run it through the model. You now have the output which will be perfectly reproduced with the same inputs.
- techpression 19d ago
  You should publish, likely a Nobel price or Turing award waiting, and generational wealth at some tech giant.
- simonw 19d ago
  By "can't predict exactly where the weights will take you next" I meant with your brain. The blind chess analogy suggests you can predict, using your own thought process, the exact output of a prompt.
  - trollbridge 19d ago
    I could use my brain to run a set weights, given enough time (on the order of millions of years).
- shakna 19d ago
andai 19d ago
>you're going to end up with a system you don't 100% understand very quickly This has been my experience with all software projects. Even if I wrote all the code, my understanding of how everything works and fits together decays. ( See the Forgetting Curves https://en.wikipedia.org/wiki/Hermann_Ebbinghaus https://en.wikipedia.org/wiki/Hermann_Ebbinghaus )
- simonw 19d ago
  Yeah, that's a fair point. I have plenty of older projects where I no longer understand how they work despite having written the code myself. I guess the key thing is that you need to be able to demonstrate to yourself that you understand the code at least once, because that means you should be able to revise how it works in the future. You also can't evaluate if a solution is fit for purpose if you don't understand it.
  - thec0d3 19d ago
    You don't buy the article's position but have forgotten a lot and not known a lot; so no need to care about your opinion I guess This is my beef with modern software engineers; complete detachment from physical reality where entropy is eroding structure (memory, generational churn). Code is just a euphemism for a desired electrical state. No need to dump biz contexts in code. Just make a game engine that efficiently handles geometry on screen and label the presentation layer. All ya'll are doing is recreating front end rendering technology, forgetting in time and recreating it in new semantics. It's absolutely fucking asinine. I look forward to models in chips and a tiny universal code base coupled to the machine. This whole allowing a bunch of unelected rhetoricians tell myself and other hardware engineers we need them to use our property is exhausting. It's rhetorical nonsense that goes in these broad loops recreating old work. Time to move on from what titillated you all as children. Or you will just end up entitled Boomers. Writing code like its 1970s is not high tech. It's old low tech
    - names_are_hard 18d ago
      This is either incredibly advanced, genius-level insight into the future of software engineering, or absolutely nonsensical gibberish. I'm not smart enough to tell which, I suppose we'll find out.
deleted 19d ago
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dumbfounder 19d ago

Meh. Chess exists to entertain the players. Coding exists to solve problems. I see way too often the programmers think it’s all about the coder and the code. Solve the problem. Don’t write code at all to do that if you can (AI generated or otherwise).

Supermancho 19d ago
Once you get past trivial problems, the issue is not just "solving the problem" but proving the solution "solves the problem". This is the strongest argument as to why AI should only be used as small solvers (at this point).
andai 19d ago
Yeah, it's about incentives. Software development is about solving business problems, but sometimes the solution is "use this thing that already exists instead of paying me to build it." Similarly, the incentive is to design it so you will need to spend 10 years working on it, instead of 10 hours.

tikimcfee 19d ago

I really like this idea, because I think people forgetting that when you are writing code there exist a time T greater than zero, where you're not actually writing code and you're doing this thing called "thinking", ha ha. I find that there's a lot of times where I'm sitting staring at the screen and the lines of text sort of blur, and I'm in my head thinking about the connection of everything and not really worried about the actual implementation and how bites are moving, but wondering about the structure and the nature of the actual flow of the code. There's a wonderful XKCD about this, where a person sitting on a computer has this very beautiful stack of thoughts and clouds about what's being written, and then someone walks up to them and says something, and the entire cloud pops. If I understand this article, I think that's exactly a reasonable analogy to it. There is something that happens in the mind, and perhaps a neural weights, where the non-execution is where creativity and problem solving happening by mapping to the higher level concepts and stitching them together without having to specifically worry about the line level details. They still crop up, and implementation will probably always be king, But I do think I agree with this entirely!

yipinwong 19d ago

Analogies work at an abstraction, and gotta take the chess analogy at its face value, as deeper people go into what's different between the chess and real life (deterministic vs non-deministic), one is not getting the lesson the author is presenting. Remember, analogy is not territory. Every analogies fail at some point

lordnacho 19d ago

I think I agree. I guess I don't know enough about chess to be sure, but the idea seems to be that although to novices a blindfolded player must reconstruct the board in his mind, that is not actually what is done by the expert. That is something I can agree with, having spent a heck of a long time coding in the trading domain. I've managed to vibe code a trading system. It's a hobby project directed on my phone on my commute, but it does do all the things I find important about trading systems. I can connect to external exchanges and see that I have sent valid orders, I get fills, and I can see debug logs of the timestamps. It doesn't allocate memory on the hot path, cores can be pinned, and so on. There are benchmarks that say how fast the code is parsing messages. It works. So I've somehow built a thing that I've barely examined in the traditional sense, which nonetheless satisfies certain business needs for this hobby project. How could that be? If you transported me back two years, I would know exactly where to make whatever changes you desired. I had the IDE open all the time, and I knew where things were. Now, I don't even know what the internal structure is like, I just know whether consideration has been made for some aspect of the system. And I think this is what seems so baffling to a lot of people. How are software developers getting such different experiences with LLMs? Some people genuinely are producing things with incredible pace, while others find the AI just produces slop for them. Some people are ready for the blindfold, but many are not. It's incredibly frustrating, especially if you are reasonably advanced but not yet at that overview stage.

deleted 19d ago
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mikeaskew4 19d ago

My dad just had a computer around and looked the other way when I spent all night on it. And I learned chess on my own. This may not be the argument Mike makes here, I have always felt that seeing the board and not knowing what it means is more valuable than knowing everything about it without seeing it. If you’re drowning, who do you want to save you, the lifeguard who can’t read or the author of the book on water lifesaving techniques who can’t swim?

yellow_lead 19d ago

Is there anything new in this article? Yes, experts use AI better than non-experts for tasks in their domain. See LLMs reward expertise [1] and Terrance Taos conversation with LLM [2]. [1] https://www.seangoedecke.com/llms-reward-expertise/ https://www.seangoedecke.com/llms-reward-expertise/ [2] https://chatgpt.com/share/6a5fdc7a-d6f8-83e8-bbea-8deb42cfed56 https://chatgpt.com/share/6a5fdc7a-d6f8-83e8-bbea-8deb42cfed...

a2ff6eeb0 19d ago
I think the need for expertise is also going away. For example, when Claude made progress on the Riemann conjecture, > Jarred's input was mostly limited to sending Claude messages of encouragement (mostly variants of “keep going” or “believe in yourself”).2 This seems to have helped Claude overcome some initial skepticism that it could make meaningful progress. https://www.anthropic.com/research/riemann-zeta https://www.anthropic.com/research/riemann-zeta The full transcript is here: https://www-cdn.anthropic.com/8a0d1add3c637b858a9a181e98c40e9548c3f44f.pdf https://www-cdn.anthropic.com/8a0d1add3c637b858a9a181e98c40e... We're on the border of fully outsourcing expertise.
- yellow_lead 19d ago
  > Two mathematicians at Anthropic studied and validated Claude’s paper, and produced an informal note for experts stating Claude’s proof concisely. No, experts are still needed
  - a2ff6eeb0 19d ago
    Yes, that's why we're on the border: AI is doing its thing without us, but we're not yet confident enough to let the AI do its thing without checking. You may notice that humans only checked the work and explained. You may also see that that the person prompting the AI, Jared of bun.js fame, is not a noted expert in mathematics.

syou1024 19d ago

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qbane 19d ago

I do not think the metaphor can go very far. Have blindfolded chess become the "productivity trend" that every one should learn it to enjoy chess? Have normal chess players been replaced because skilled players can do blindfolded?

deleted 19d ago
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a2ff6eeb0 19d ago

This makes no sense. The skills needed for AI coding are the same skills needed to hire Gary Kasparov to play chess. Tell them where the game is and stand back as they play.

F7F7F7 19d ago

This article reads like it was written by prompting AI for connections between two loosely connected things.

brazukadev 19d ago
No, this article does not look like it was written by prompting AI just because you didn't like it.

TZubiri 19d ago

Au contraire, playing blindfold is removing a tool, depending on nothing but your mind. Vibe coding is the opposite, not just depending on the chessboard, but depending on a couple of Gflops to even think. Blindfolded programming would be the programming we do in the shower

_diyar 19d ago

The analogy can be dragged one step further: once the engine is good enough, it’s functionally impractical for a human to play.

dimitarbogdanov 19d ago
I disagree. A chess engine has a very well defined goal and is working its patterns to reach that goal. In software development, except in a minority of cases, the goal is being set by non-technical people, who have no clue how the resulting system should end up, only what it should look like to a user. I think a well-versed programmer can give the AI direct instructions on how to implement something, and just let the LLM write the code to implement/refactor the infrastructure behind the feature they're developing. For me the plan mode of Claude Code is (anecdote incoming) much faster(TM) and better(TM) if I give it concrete instructions - then it writes the plan, asks questions - and then implements it. Very little complaints after that (I usually don't let Claude do any sort of visual QA)

dzonga 19d ago

it's a Sunday - I don't have time to put things into buckets. there's coding - writing code to do something could be a game, utility to move files around. what have you. inherently the nature is a closed domain. AI is perfect here - the impact if something goes wrong is close to 0 or null. then there's software engineering - which is both an art & science. u r dealing with rules of thumb. nothing is ever coded / written down. but a feel to whether something feels right or not. the domain is unbounded. the impact of something going wrong is catastrophic in all dimensions. coding is a delivery mechanism for software engineering. but not the actual work. using A.I here is useless. but we keep having these pieces - I guess that's just shallow the industry is.

mistrial9 19d ago

William E. "Bill" Bates in Berkeley coded an entire "virtual cat" demo in the late-1990s on the MacOS using neural nets and learning. source: eye-witness

paidx 19d ago

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lowbloodsugar 19d ago

I use AI every day and have unlimited budget. I will certainly not trust it to write safe, system level code for our systems. You absolutely do need to be playing blindfold chess and you can’t do that if the other actor doesn’t tell you the moves it made. Using LLMs as described here is essentially what vibe coding is all about. To use this chess analogy, the model says “checkmate!” and you just believe it because you never heard or looked at the moves it claimed to have made.

cryptolobster 19d ago

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jpollock 18d ago

If you can't look at the code, you need to trust interfaces to specify (and constrain) the implementation. The implementation needs to implement the entire interface and can't do anything not in the interface. Otherwise, you're going to get bit by the Law of Leaky Abstractions. The number of times I've been bit by systems not adhering to interfaces? Yeah, that's pretty frequent. For example (from personal experience), the interface allows for race conditions, it's obvious they can happen (distributed systems), but the implementation didn't allow them, resulting in fun times.

sshine 18d ago

> if a seasoned programmer sits behind Claude Code, the quality output will likely be higher than if a non technical person does it Anecdotal: I recently rewrote a service in Rust for a much needed 100x performance boost (largely due to architectural changes, somewhat due to better runtime). My colleague who now maintains the app is not a Rust developer and knows little about threads and tokio. Debugging a problem, he said he’d reach the context window before pinning the problem. I never have that problem and effortlessly find problems in the first 100k tokens without trying. The difference must be in the wording that initially guides the agent.