ah i see so you're saying that LLM-written code is already showing signs of being a maintenance nightmare, and that's a reason to be skeptical about its adoption. But isn't that just a classic case of 'we've always done it this way' thinking?
legacy code is a problem regardless of who wrote it. Humans have been writing suboptimal, hard-to-maintain code for decades. At least with LLMs, we have the opportunity to design and implement better coding standards and review processes from the start.
let's be real, most of the code written by humans is not exactly a paragon of elegance and maintainability either. I've seen my fair share of 'accidentally quadratic algorithms' and 'subtly wrong code that looks right' written by humans. At least with LLMs, we can identify and address these issues more systematically.
As for 'un-idiomatic use of programming language features', isn't that just a matter of training the LLM on a more diverse set of coding styles and idioms? It's not like humans have a monopoly on good coding practices.
So, instead of throwing up our hands, why not try to address these issues head-on and see if we can create a better future for software development?
Maybe it will work out, but I think we’ll regret this experiment because it’s the wrong sort of “force accelerator”: writing tons of code that should be abstracted rather than just dumped out literally has always caused the worst messes I’ve seen.
Yes, same way that the image model outputs have already permeated the blogosphere and pushed out some artists, the other models will all bury us under a pile of auto-generated code.
We will yearn for the pre-GPT years at some point, like we yearn for the internet of the late 90s/early 2000s. Not for a while though. We're going through the early phases of GPT today, so it hasn't been taken over by the traditional power players yet.
legacy code is a problem regardless of who wrote it. Humans have been writing suboptimal, hard-to-maintain code for decades. At least with LLMs, we have the opportunity to design and implement better coding standards and review processes from the start.
let's be real, most of the code written by humans is not exactly a paragon of elegance and maintainability either. I've seen my fair share of 'accidentally quadratic algorithms' and 'subtly wrong code that looks right' written by humans. At least with LLMs, we can identify and address these issues more systematically.
As for 'un-idiomatic use of programming language features', isn't that just a matter of training the LLM on a more diverse set of coding styles and idioms? It's not like humans have a monopoly on good coding practices.
So, instead of throwing up our hands, why not try to address these issues head-on and see if we can create a better future for software development?