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192 points imasl42 | 1 comments | | HN request time: 0.2s | source
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rsynnott ◴[] No.45311963[source]
This idea that you can get good results from a bad process as long as you have good quality control seems… dubious, to say the least. “Sure, it’ll produce endless broken nonsense, but as long as someone is checking, it’s fine.” This, generally, doesn’t really work. You see people _try_ it in industry a bit; have a process which produces a high rate of failures, catch them in QA, rework (the US car industry used to be notorious for this). I don’t know of any case where it has really worked out.

Imagine that your boss came to you, the tech lead of a small team, and said “okay, instead of having five competent people, your team will now have 25 complete idiots. We expect that their random flailing will sometimes produce stuff that kinda works, and it will be your job to review it all.” Now, you would, of course, think that your boss had gone crazy. No-one would expect this to produce good results. But somehow, stick ‘AI’ on this scenario, and a lot of people start to think “hey, maybe that could work.”

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1. altspace ◴[] No.45322932[source]
What I took away from the article was that being good at code review makes the person better at guiding the agent to do the job, giving the right context and constraints at the right time… and not that the code reviewer has to fix whatever agent generated… this is also pretty close to my personal experience… LLM models are a bull which can be guided and definitely not a complete idiot…

In a strange kind of analogy, flowing water can cause a lot of damage.. but a dam built to the right specification and turbines can harness that for something very useful… the art is to learn how to build that dam