Reduce is harder to read. Maps and filters are deeply simple. The problem space a reduce can solve is, I’m pretty sure, strictly larger than both of them. Its generality is its downfall.
I’ll happily use a reduce, but it has to be either as a well named function or immediately stored in a well named variable. If the reduce is complex enough that you can’t name it, that’s a smell to me, reach for a different tool.
That doesn’t change the fact that it’s harder to properly review code than to write code, especially when that code is ten times longer than it needs to be, makes no sensible decisions about how to separate concerns, and might, if you’re lucky, pay lip service to naming things well.
I don’t necessarily think this will always be the case with generated code, but I expect we’ll need a proper breakthrough in the technology before it can write good code (it needs a number of things: actual world models, the ability to go back and edit its output when it realises a mistake – which is crucially different from saying a new thing that contradicts the mistake – and continual learning, to name the three that spring to mind).
Even if it started writing perfect code, I’d be dubious of signing your org’s ability to write code away to a service that you don’t own and has a notable history of intellectual property infringement and an insane disregard for both the law and morality. At the very least we should all be using open weights models.
It is a very well known truism that it is harder to debug code than it is to write it. This is, in my experience, doubly true of the convoluted code generated by current frontier LLMs.
Allowing LLM coding at our org basically stole most of this year’s progress from us as every PR made this way still has yet to be merged because the code quality just never reaches anywhere near our minimum requirement.
We are investigating ways to improve this (a style guide for agents etc) but the best step we’ve taken so far is just to ask people to stop using it and see what happens. (Code quality jumped up and PRs started getting merged, though the LLM ones are still languishing and probably will need rewriting from scratch before we can merge them)
Seems to be polynomial growth, actually: https://en.wikipedia.org/wiki/Fourth_power_law
Which makes more sense, but still; a 44 tonne lorry is doing 44^4 times as much damage as a 1 tonne car, which is 3.7 million times as much.
I assume the exponential doesn’t hold up for some reason, maybe because of the amount of wheels they have. Otherwise it would seem that an LGV (maximum weight to cross borders in the EU is 44tonnes), would deal 16^44 times as much damage as a normal car, which is a large enough ratio that I think it would be safe to say that either the road would be immediately obliterated under any vehicle of that weight or normal cars do so little damage that it would be misleading to represent it as anything other than zero.
To be clear: I’m not trying to say you’re wrong. There’s another option for the growth rate, given the two data points given, that probably makes more sense. I just found it amusing to entertain the thought and go through the process.
Given how much heavier freight vehicles are than any passenger car, what percentage of road damage do they cause, given the damage seems to grow at O(n^16) ?
This was written by ai, right?