| ▲ | listic 14 hours ago | ||||||||||||||||||||||
Do yo have links handy for AI-assisted engineering going positively? The case I have on my mind of it going negatively is this recent Ford case [1] It's not that I believe it couldn't go positively, of course. [1] Ford rehires human engineers after AI fails to match quality checks | |||||||||||||||||||||||
| ▲ | simonw 13 hours ago | parent | next [-] | ||||||||||||||||||||||
That Ford story was really misleading. It wasn't about modern LLMs, and the way it was reported implied that Ford had fired and then hired people but if you read closer that wasn't necessarily the case at all - it sounded more like they were re-hiring people who had retired because they needed expertise that had left the company. You need to get through the Bloomberg paywall: https://www.bloomberg.com/news/articles/2026-06-25/ford-has-... > Over the last three years, Ford says it has hired 350 veteran engineers, many of them former employees and others from suppliers, to help address seemingly intractable quality woes that have cost the automaker billions. [...] > “We had been relying more and more on automated quality systems” and not getting the desired results, Galhotra said. “We brought back technical specialists” and “they hunt for failure points before a part ever reaches the plant floor.” (I made these points on the HN thread about it 3 weeks ago and got voted down and I'm still salty about it https://news.ycombinator.com/item?id=48674446#48675045 ) | |||||||||||||||||||||||
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| ▲ | jdlshore 12 hours ago | parent | prev | next [-] | ||||||||||||||||||||||
As @simonw said, the Ford example isn’t a good one. As for AI-assisted engineering going well, I think the jury is still out. Here on HN and with the engineers I know, you see people claiming multiples of productivity on coding tasks. But you also see people complaining about drowning in slop PRs. I think there’s a lot of confounding factors to these reports. The type of work matters a lot: bug fixing good, prototyping good, big legacy codebases not so much, but maybe good for increased understanding. The type of automation matters: aggressive autocomplete good, vibe coding bad, dark factory (vibe coding with fancy harnesses and auto-“correcting” eval loops) questionable. And then finally, the perennial mistake our industry makes, which is to value speed of creation over maintenance costs. Personally, I think this is where AI-assisted engineering is going to fall down really hard, but the jury’s still out on that one. Anyway, there’s a really big spread in experiences with AI, that I think chalk up more to all this context rather than religion and belief. OP didn’t address it at all, which I think is a big gap in their essay, but I do think think they describe the executive-level mania pretty well. | |||||||||||||||||||||||
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| ▲ | prodigycorp 13 hours ago | parent | prev [-] | ||||||||||||||||||||||
The Ford case is not about AI coding. It's about computer vision processes that went wrong. This was less about AI and more about Ford being dumb. | |||||||||||||||||||||||