In other words, because GEN AI a lot of code, the idea is to shift human value toward verification. Sometimes I think about what programming really is. In fact, learning programming itself is a huge challenge for a non English speaker like me. I have to rely on machine translation to understand English documents that have no translation. The materials in my language are about 5 to 6 years behind.

Now, since it's impossible to code review the tens of thousands of lines of code that AI produces, I see discussions about establishing an absolute rule like mathematical proofs. Reading this reminds me of Rust's borrow checker. In fact, after writing in Rust a few times, it often leads to bad practices where people use tricks to avoid the borrow checker.

Actually, when mathematical rigor goes too far, humans tend to find ways around it. An undereducated programmer like me is especially prone to that.

Looking back at this kind of attempt, it will probably result in writing code only for specific formalized answers. If it becomes that standardized, I'm not sure it will be able to respond to human needs.

I think these defensive programming attempts are fine, but I want to do offensive programming (I coined that term). You take risks, but you fix things quickly and ship. Believing that over time, it will become good enough. Of course, for established industries where accuracy matters and the scope of work is well defined, like Jane Street, the approach in this article is correct. In other words, because there is enough data to adequately model the market's demands

But for social losers like me trying to make money, constantly moving from place to place looking for gold mines, these kinds of methodologies seem like a luxury.Established businesses with mature modeling need highly educated and specialized personnel to continuously optimize. But I know that realistically, I can't keep up with that demand. So I look for places where modeling is unstructured, but I'm not sure if I can use this approach even then.

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ngruhn 2 hours ago | parent | next [-]

> I want to do offensive programming (I coined that term). You take risks, but you fix things quickly and ship.

Nice, I like the term too. But the paradigm is absolutely status quo in the industry. The thing is: with Gen AI the cost of "defensive programming" has gone way down, while the cost of (human) verification has gone way up. On the other hand, formal methods make verification cheap but come with massive implementation overhead (writing specs, types, proofs, and generally bending the implementation into a rigid framework). But Gen AI can automate all that laborious work. It's a match made in heaven.

	▲	jdw64 an hour ago \| parent [-]
		You're right. I think the point we need to discuss here is, to be clear, dividing the contexts in which defensive programming is strong and where it should be aggressive. I think the overhead of implementation is enormous, but I believe AI can write it. However, before even reaching the 'implementation' stage, that is, at the planning stage, sufficient data must be collected for the implementation to be safe. In that respect, I think Jane Street already has enough data and modeling capabilities. However, I think it's a bit difficult to say whether this approach will take shape in many other domains. In that sense, I also think that the reason many industries are doing this kind of fast deployment and experimental tooling might be a preparatory step for that kind of modeling. Have a good day Thanks for the good comment. It helped me think more sharply as well

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stephenlf 5 hours ago | parent | prev [-]

> these kinds of methodologies seem like a luxury

Absolutely. The article acknowledges this. Jane Street is pretty uniquely equipped to benefit from this.