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It is interesting that the output of code is associated with sight and taste, while the quality of the code itself is associated with smell.

https://en.wikipedia.org/wiki/Code_smell

*edit: that wikipedia page ^ itself is a pretty answer to your request for a list of things to avoid when writing maintainable code.

by degamad22 minutes ago|

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I think that's because you can usually smell when food is close to being rotten before you can see it...

EDIT: reading the WardsWiki reference from that Wikipedia page, there's also the point made by early users of the term that smells are something you have to check out, but don't always mean something needs fixing - e.g. a bad smell may be a gas leak, or it may just be a rubbish bin.

by blanched2 hours ago|

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Pairs nicely with the fact that smell is the sense most likely to be experienced differently between two people :)

by chowells8 minutes ago|

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Is that actually true? Just because English treats scents as only describable by analogy doesnt mean all languages do. There are a number of languages with scent descriptions for aspects of a smell that are transferrable. [1] That suggests everyone is capable of decomposing a scent into components the same way.

If that's true, we're left with a question equivalent to "does everyone see the same red?". As far as I know, the pure version of that question cannot be answered because subjective experiences of sensation cannot be transferred. And at that point, I'd say the manner in which they're experienced differently is equivalent.

1. https://youtu.be/w3KswMaEBiI

by nicoty2 hours ago|

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I've codified mine into a reusable workflow https://github.com/nothingnesses/agent-scaffold . To be honest, this isn't fool-proof though, since the agents can simply choose to ignore them, so I also like to pair this with deterministic linting and compile time checking.

For a Rust project, I created macros that output compiler errors when documentation and tests are not in a shape I want them to be, like missing function invocations or assertions, which forces the agent to address them, where otherwise they would've just worked around them by adding stupid trivial assertions like `assert_eq!(true, true)`.

That still isn't fool-proof either, but it helps minimise those instances. I'm bullish on the idea of integrating formal methods and model-checking with AI. I think that combo feels like a promising avenue for constraining the stochastic side of AI-generated code with something closer to deterministic verification. Provided you can write correct specs of course!