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Cake day: June 12th, 2023

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  • You’d put the things that aren’t up to personal preference in there, like an AI disclosure / contribution policy or what changes should look like to be reviewable. You usually don’t need to tell humans “don’t change things for the sake of changing them” because we don’t like to do more work than we have to, but agents do.

    You can also include a compact “table of contents,” describing what lives where in the project. It saves at most a little bit of exploration though so I don’t know if it’s really worth the maintenance










  • Gotta add context for readers.

    Of all the numbers to call boring you picked the Grothendieck prime.

    2 is unambiguously prime. The best motivation for the definition of primality I know is the fundamental theorem of arithmetic: every integer greater than 1 can be uniquely decomposed into a product of primes. That’s what primes are, and the uniqueness constraint is why 1 is not prime.


  • That doesn’t follow. What I think you mean is that by defining the constraints so rigorously, you’ve basically solved the problem yourself. But that’s exactly the point. The LLM isn’t the problem solver, it’s the execution engine that does the wiring-up and the ticking of boxes. The easy part, arguably, sure. But still considerable effort that can be saved, and that effort may be better spent on the problem-solving + constraint-defining stage.

    Mandatory disclaimer that this is not a pro-AI post. I also don’t agree that this setup works, anyway. It’s a classic Bob Martinism, the idea that writing good enough specifications makes the implementation irrelevant; it’s the type of idea that is allergic to reality