Are LLMs getting much better at coding? The new models are arguably better at understanding context and coming up with a solution that works but they still write just as much hilariously bad or hacky code as the models did 2 years ago. I e.g. ask Fable 5.1 to make changes to my software and if it's something that's not a standard CRUD architecture on top of a well-specified library it will come up with pretty wild stuff, i.e. producing shell scripts with a "cat" command that contains a 1,000 line Golang program that it compiles on the fly to load some data, or a whole Javascript tool it crams into a string in a server-side web app to make some UI element work instead of figuring out how to do it "right". Another model wrote its own (buggy) YAML parser for reading translations and I had to figure out why it broke my whole pipeline (can't even say why it chose to write that instead of just reusing a standard library, maybe I told it before to be careful when adding untrusted dependencies so it interpreted it as writing everything itself). Seems these systems are always trained to produce the desired output but I think it's very difficult to get training data that teach the systems how to keep the code maintainable when making hundreds or thousands of such individual edits. Honestly not sure if that will get better fast, so far it seems not!

I guess there's no reason to believe these models can't be as smart as a great software architect / engineer or team of such people that build an elegant and maintainable software solution over many years together based on customer feedback, then again the models are appallingly bad at some forms of reasoning, I mean they will "understand" something once you make them aware of it like e.g. a flaw in the software architecture, but when asking them to audit the code and check for issues they will often have a blind spot to finding such problems. It's interesting, like they have very high ability but very little awareness or self-directed thinking outside of the prompts they receive.