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192 points imasl42 | 1 comments | | HN request time: 0s | 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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Manfred ◴[] No.45312253[source]
Reviewing code from less experienced or unmotivated people is also very taxing, both in a cognitive and emotional sense. It will never approach a really good level of quality because you just give up after 4 rounds of reviews on the same feature.
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1. btown ◴[] No.45324333[source]
Here’s the thing about AI though - you don’t need to worry about its confidence or impact on professional development if you’re overly critical, and it will do a turn within seconds. That gives a tremendous amount of flexibility and leverage to the code reviewer. Works better on some types of problems than others, but it’s worth exploring!