Why supply underspecified requirements in the first place? Both models are good at challenging assumptions/edge cases and asking questions to clarify, but seemingly only when explicitly asked (i.e. something like a "brainstorm" skill).

I don't think either harnesses do enough to encourage the model to challenge all assumptions and ask questions, maybe because users might find it annoying. That step is basically a requirement IMO.

I've found all of the GPT-5 models to be very nit-picky, useful for code review and mathematics (important for my work), but seemingly gets in the way of "aesthetic" code, e.g. overly defensive code to cover all edge cases, even if unlikely.

There is seemingly also a tradeoff between flexibility vs instruction following. In my experience Opus will sometimes ignore instructions but can "fill in the blanks" more, vs GPT-5.5 follows instructions better but perhaps at the cost of rigidity.

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fooker an hour ago | parent | next [-]

> Why supply underspecified requirements in the first place?

Because you'd not want to forever loop outside your home when asked to "while you're out, grab some eggs" :)

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antonvs 2 hours ago | parent | prev [-]

> Why supply underspecified requirements in the first place?

Minimizes effort, is the obvious answer.

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cyberpunk an hour ago | parent [-]

Poor trade off, the model is then designing a massive chunk of your solution instead of you. With a good spec, bits of typo’d pseudocode, and slightly more effort than a couple of sentences they can actually produce passable software.

I think the reason claude has so much mindshare is exactly because it’s more useful to non-developers who wouldn’t know how to describe what an api call executes to his grandmother.

For those who can, I can’t find much of a difference between them. Codex has the slight edge, but that’s all just “feels” to me.

	▲	ben_w 6 minutes ago \| parent [-]
		You call it a poor trade off, but: > I think the reason claude has so much mindshare is exactly because it’s more useful to non-developers who wouldn’t know how to describe what an api call executes to his grandmother. This is exactly the benefit for most people. Most people don't want to code the app, they just want the app. Even people like us who do like coding, we can only think of all of these things within a domain that we already know; somebody who writes shaders for games isn't likely to know or care much about the ins and outs of database development or how healthcare privacy law and KYC interact with zero-knowledge proofs. (Of course, if the AI knows about these things and then completely fails to make use of that knowlege, that's still a fail).