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Comment by meowface | Hacker News Reader

GPT-5.5 is the better programmer but Opus 4.8 remains the better system architect and product designer.

Codex is very "miss the forest for the trees", but is much better at successfully making large changes in large codebases. Claude Code makes more mistakes, but has more taste and a better grasp on idiomatic and elegant software development.

If you can afford to, I recommend juggling both.

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Great analysis and follows my experience as well. Codex is better when you know how you want the design and the architecture and you drive the agent a lot more aggressively. Claude Code feels like more autopilot so executives and users who didn’t code before AI like it a lot more.

But I feel like an expert who can drive GPT aggressively will out perform Opus. It’s why some smart people I know are opting for GPT and have fallen off on Opus. It’s like asking an F1 driver to sit in a taxi.

This is exactly right. Claude has baked in autonomy and preferences that let it handle underspecified prompts elegantly, which makes it seem smarter to people who like to prompt that way, but it also ignores instructions and fights you on things, which makes it a bad model for people who know what they want to do and specify it.

Opus 4.7 (haven't tried 4.8) just really struggles writing correct code for complicated (i.e. valuable) work. I can handle architecture, which takes <1% of my time anyway. But writing code that's wrong is a cardinal sin. I've had much more luck with GPT 5.5 so far.

I find arguing that a complex weighted graph has a taste is interesting.

This is not a jab, but a genuine curiosity of mine.

The taste that the complex weighted graph was trained on was better for one than the other I think is the long winded way to say it

The roulette pockets for the model are bigger for some outputs than others. Draw a big enough black box around it and a different one around humans and it's insistinguishable.

More interesting than arguing a jumble of electrochemical reactions have taste? That may seem more readily familiar but is no less strange if you prod at it. Nonetheless it’s difficult to argue either don’t produce output that has qualities of discernment (ie taste).

Isn't it just arguing that one complex weighted graph was tuned to output tokens that more align with what current day users would define as 'taste'?

I don't think it necessarily says anything about a model itself having 'taste' in some subjective way.

If the fashion changes would the model update with it without retraining? No. So the model doesn't have 'taste' in that sense. It has alignment to current human definitions of taste.

It is more capable of writing code I find tasteful and maintainable. It is debatable to what extent it itself has taste. Its outputs just suit my taste more than Codex's do, even though Codex introduces fewer bugs.

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