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What my dad taught me about AI coding in the 90s
21–30 of 91 posts
Re: What my dad taught me about AI coding in the 90s
#22Earlier quoted context omitted.
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 Cod…
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.
> 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?
Re: What my dad taught me about AI coding in the 90s
#23I 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?
Re: What my dad taught me about AI coding in the 90s
#24This 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.
Re: What my dad taught me about AI coding in the 90s
#25This article reads like it was written by prompting AI for connections between two loosely connected things.
Re: What my dad taught me about AI coding in the 90s
#26I'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 suppo…
>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 )
Re: What my dad taught me about AI coding in the 90s
#27I'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 suppo…
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 “wi…
Could you give some examples?
Re: What my dad taught me about AI coding in the 90s
#28Is 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/ [2] https://chatgpt.com/share/6a5fdc7a-d6f8-83e8-bbea-8deb42cfed...
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
The full transcript is here: https://www-cdn.anthropic.com/8a0d1add3c637b858a9a181e98c40e...
We're on the border of fully outsourcing expertise.
Re: What my dad taught me about AI coding in the 90s
#29Meh. 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).
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.
Re: What my dad taught me about AI coding in the 90s
#30Earlier quoted context omitted.
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 “wi…
Floating point matrix calculations are non-deterministic. You need to invent new hardware, that doesn't use floating point math, first. [0] [0] https://arxiv.org/html/2506.09501
>Floating point matrix calculations are non-deterministic.
This is not inherent to floating-point math. That actual (true) claim in the article is that different hardware and different hardware configurations produce different results. But deterministic inference is possible, e.g. llama.cpp on CPU is deterministic by default.