What my dad taught me about AI coding in the 90s
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Re: What my dad taught me about AI coding in the 90s
#2In 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.
Re: What my dad taught me about AI coding in the 90s
#3I'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…
| 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.
Re: What my dad taught me about AI coding in the 90s
#4Re: What my dad taught me about AI coding in the 90s
#5I'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…
> 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).
Re: What my dad taught me about AI coding in the 90s
#6I'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…
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).
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.
Re: What my dad taught me about AI coding in the 90s
#7Earlier quoted context omitted.
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).
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.
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.
Re: What my dad taught me about AI coding in the 90s
#8I'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 “will take you” given a set of inputs.
Re: What my dad taught me about AI coding in the 90s
#9I'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…
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…
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.