The need to select an appropriate 3rd party library represents an entire dimension of the search space that can be eliminated. Imagine having to make this choice multiple times per day when your competition is just mindlessly using System.* types. The fact that the .NET ecosystem is curated by one entity should not be underestimated.
Even when we do need to import 3rd party nugets, the models seem to follow this highly structured pattern. They scan the xml docs, and failing that they will build a throwaway console app to reflect over all the unique types and build a report. The fact that we can easily do this with a simple powershell command makes a big difference. How many other ecosystems can even consider doing this? Reflection is a superpower, not something to be avoided.
Reflection is just such a dangerous feature that looks like ordinary code, which is why it is something to be avoided, and having an LLM write/analyze the code for eliminates the need to use a lot of reflective code to begin with.
Another slept-on feature is the ability to quickly write your own static analyzers, which along with the myriad of existing analyzers out there, provide excellent guard-rails to prevent slop.
For existing codebases I made the experience, that LLMs are very good at replicating their style.
At work most of our C++ codebases use a fairly consistent style and subset of C++ features and to my initial surprise specifying style conventions etc explicitly turned out to be mostly superfluous.
Of course, we also have some legacy projects originally, written in ANSI C, which only received a few changes in the last 15 years to compile with a C++ compiler. Here a style guide is helpful, bit I consider it more like a temporary instruction for refactoring.
However, I struggle as well and the error messages of Oracle are some of the worst I've ever experienced.
And yet this article has pretty strong empirical data to show that your intuition here is incorrect. You should back up your statement with something more than vibes.
My experiences are of course anecdotal, but if you have some other strong empirical data to show, I'd love to see it.
Is the claim that LLMs produce Go code that is superficially nice looking but in fact fail to solve the stated problem? Because that's an anti-Go position I'd say.
Correctness is a suitable property to act as a multiplier in your formula, where incorrect is 0 and correct is 1, but you also need other facets to find a quality gradient.