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lukemercado • today at 12:56 AM • 4 replies • view on HN

The incredible engineering in the hardware is prized above software quality.

For most companies I'd say this is a natural tradeoff, but Apple has so much money that they can actually afford to be world class in both. Or at least, you'd expect they could. Maybe being world class in software would require delays to the hardware side of the business?

Regardless, it's definitely a weakness of the culture and I'd venture that weakness is why Apple has essentially failed at AI.


Replies

Barbing • today at 2:34 AM

> Apple has so much money that they can actually afford to be world class in both

This is what gets me. Think about only bugs, not a single wishlist feature, just bugs. Limit to obvious-to-normies defects: so, UI bugs (ultra-low contrast oddity with certain backgrounds while scrolling lock screen notification center) or popular-feature bugs (AirDrop demands “everyone“ to receive from people in contacts, apparently in at least a couple cases).

At least in the case of UI bugs, no secret sauce seems to be required to resolve them. No particularly special feats of engineering. It seems simply dollars can fix them: QA & engineering. When I discover these obvious defects, update iOS multiple times over the course of months, and continue to experience them, I can only assume Apple prioritized having cash on hand over investing in my (our) experience.

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appplication • today at 1:07 AM

Having recently worked at Apple on the software side, my general experience was that it was fiefdom driven, there is no internal standardization on quality or process. Low level teams compete on ideas and careful politicking usually wins over quality or merit.

For AI, there were top down directives to find new ways to experiment with and incorporate into core products and processes, but as you went down the management chain, management became more conservative. First and second line managers were strongly incentivized to keep their products, roadmaps, and interfaces stable and predictable by similarly conservative stakeholders. And as such, they were generally unwilling to officially dedicate much effort to AI other than the minimum “look at how much we’re using Claude”.

In particular due to the lack of central tooling, any team trying to do much with AI essentially had to reinvent much of the stack themselves. So even small projects were largely untenable due to inevitable required scope creep.

functionmouse • today at 2:30 AM

> The incredible engineering in the hardware is prized above software quality.

then let me root and customize the software to my liking

prpl • today at 1:13 AM

Big E Engineering vs little e engineering.

IMO the barriers to entry are just much different, and it’s reflecting in the workforce. There’s cultural differences too, but I think the education differences is the biggest cause.

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