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Ford had to hire back former engineers to fix mistakes made by its automated systems
(www.theverge.com)
this post was submitted on 25 Jun 2026
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I've been using an LLM for programming for last 6mo and it needs constant babysitting. It's basically something that just does the most straightforward thing without consideration of nuance, maintainability or whether to actually split into a module. This is very much not surprising.
Yeah, I use it for some programming tasks as well. I’m sick and tired of telling it that it did something wrong or simply omitted something, only to have it apologize and offer to fix its own mistakes.
The major problem is that the work of an LLM has a massive number of hidden 'assumptions' that you need to be aware of. If you don't already have a good working knowledge of the task you wont have an intuition about those assumptions. It's annoying.
Yeah, and for those who don't know, the rationalization output of the LLM is just so pursuasive. It sounds quietly confident and rattles off things that sound like real details.
People are believing the LLM output over actual human experts and the human experts have to expend non-trivial effort trying to disprove an LLM output before they can get on with the business of doing it right.