this post was submitted on 24 Jun 2023
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Programming
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I'm dealing with a new service written by someone who extensively cut and pasted from ChatGPT, got it to "almost done -- just needs all the operational excellence type stuff to put it into production", and left the project.
Honestly we should have just scrapped it and rewritten it. It's barely coherent and filled with basic bugs that have wasted so much time.
I feel maybe this style of sloppy coding workflow is better suited to front end coding or a simple CRUD API for saving state, where you can immediately see if something works as intended, than backend services that have to handle common sense business logic like "don't explode if there is no inventory" and etc.
For this dev, I think he was new to the language and got in a tight feedback loop of hacking together stuff with ChatGPT without trying to really understand each line of code. I think he didn't learn as much as if he would have applied himself to reading library and language documentation, and so is still a weak dev. Even though we gave him an opportunity to grow with a small green field service and several months to write it.
I wouldn't consider the bugs chatgpt's fault, per se. The same could happen by blindly copy/pasting from SO or a template Github project. If you are copy/pasting from anywhere, it's even more important that you have good automated tests with good coverage, and that you take extra time to understand what you pasted.
One of the things I do is generate high level tests first, and then the implementation code. This way I know it works, and I can spend extra time reviewing the test code first to make sure it has the correct goal(s).
Learning is another matter. Personally, ChatGPT has greatly accelerated my learning of libraries and other languages. I've also used it to help me grok a block of complex code, and to automatically comment and refactor complex code into something more understandable. But it can also be used as a crutch.