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Comment by worldsayshi | Hacker News Reader

This is of course bad but: humans also makes (different) mistakes all the time. We could account for the risk of mistakes being introduced and make more tools that validate things for us. In a way LLM:s encourage us to do this by adding other vectors of chaos into our work.

Like, why not have tools built into our environment that checks that links are not broken? With the right architecture we could have validations for most common mistakes without having the solution adding a bunch of tedious overhead.

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In the above kind of described situation, a meticulous coder actually makes no mistakes. They will however make a LOT more mistakes if they use LLM's to do the same.

I have already had to correct a LOT of crap similar to the above in refactoring-done-via-LLM over the last year.

When stuff like this was done by a plain, slow, organic human, it was far more accurate. And many times, completely accurate with no defects. Simply because many developers pay close attention when they are forced to do the manual labour themselves.

Sure the refactoring commit is produced faster with LLM assistance, but repeatedly reviewing code and pointing out weird defects is very stressful.

A meticulous coder probably wouldn't have typed out 40 URLs just because they want to move them from one file to another. They would copy-past them and run some sed-like commands. You could instruct an LLM agent to do something similar. For modifying a lot of files or a lot of lines, I instruct them to write a script that does what I need instead of telling them to do it themselves.

> I have already had to correct a LOT of crap similar to the above in refactoring-done-via-LLM over the last year

The person using the LLM should be reviewing their code before submitting it to you for review. If you can catch a copy paste error like this, then so should they.

The failure you're describing is that your coworkers are not doing their job.

And if you accept "the LLM did that, not me" as an excuse then the failure is on you and it will keep happening.

I think it goes without saying that we need to be sceptical when to use and not use LLM. The point I'm trying to make is more that we should have more validations and not that we should be less sceptical about LLMs.

Meticulousness shouldn't be an excuse to not have layers of validation that doesn't have to cost that much if done well.

LLMs are turning into LLMs+hard-coded fixes for every imaginable problem.

Why hard coded?

I agree, these kinds of stories should encourage us to setup more robust testing/backup/check strategies. Like you would absolutely have to do if you suddenly invited a bunch of inexperienced interns to edit your production code.

Your point to not rely on good intentions and have systems in place to ensure quality is good - but your comparison to humans didn't go well with me.

Very few humans fill in their task with made up crap then lie about it - I haven't met any in person. And if I did, I wouldn't want to work with them, even if they work 24/7.

Obligatory disclaimer for future employers: I believe in AI, I use it, yada yada. The reason I'm commenting here is I don't believe we should normalise this standard of quality for production work.

> that checks that links are not broken?

Can you spot the next problem introduced by this?

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