If you just let it do a full rewrite again and again, what protects against breaking changes in the API? Software doesn’t exist in a vacuum, there might be other businesses or people using a certain API and relying on it. A breaking change could be as simple as the same endpoint now being named slightly differently.
So if you now start to mark every API method as “please no breaking changes for this” at what point do you need a full software developer again to take care of the AI?
I’ve also never seen AI modify an existing code base, it’s always new code getting spit out (80% correct or so, it likes to hallucinate functions that don’t even exist). Sure, for run of the mill templates you can use it, but even a developer who told me on here they rely heavily on ChatGPT said they need to verify all the code it spits out, because sometimes it’s garbage.
In the end it’s a damn language model that uses probability on what the next word should be. It’s fantastic for what it does, but it has no consistent internal logic and the way it works it never will.
Puzzle_Sluts_4Ever@lemmy.world 1 year ago
You are literally describing constraints. They can be applied to an LLM the same way they can be applied to a dev team. And if you have never had to report an API change that breaks functionality… I wish I was you.
And if your full time software engineers are just running a unit test suite all day? … are you hiring?
As for modifcations: Again, have you ever used an LLM? Have a conversation with chatgpt. It will iterate on its responses. That is iterating on code.
And that is demonstrably false and mostly just highlights that you don’t know what you are talking about. Or what language is, for that matter.
Vlyn@lemmy.zip 1 year ago
Mate, I’ve used ChatGPT before, it straight up hallucinates functions if you want anything more complex than a basic template or a simple program. And as things are in programming, if even one tiny detail is wrong, things straight up don’t work. Also have fun putting ChatGPT answers into a real program you might have to compile, are you going to copy code into hundreds of files?
My example was public APIs, you might have an endpoint
/v2/devicethat was generated the first time around. Now external customers/businesses built their software to access this endpoint. Next run around the AI generates/v2/applianceinstead, everything breaks (while the software itself and unit tests still seem to work for the AI, it just changed a name).If you don’t want that change you now have to tell the AI what to name things (or what to keep consistent), who is going to do that? The CEO? The intern? Who writes the perfect specification?
Puzzle_Sluts_4Ever@lemmy.world 1 year ago
Yes. ChatGPT is not perfect. Because it is a general purpose LLM. Stuff like Github CoPilot and other software specific approaches are a LOT better at avoiding all the noise from bad answers on stack overflow and proposals.
But it can still do a remarkably good job so long as you have a human looking at it after the fact. Which… is how I would describe most software engineers I have ever worked with. Even the SSEs need someone to review their code. Which… is what is being described here. Combine that with a gitlab runner and you got yourself a stew.
As for APis and the like: Again, it feels like nobody here has ever actually worked with public software and think regressions don’t exist. But this is literally constraints and would be put in the requirements document that you give either the dev team or the LLM.
As for who is going to make that document: The same people who already do? Management.
Vlyn@lemmy.zip 1 year ago
Management and sound technical specifications, that sounds to me like you’ve never actually worked in a real software company.
You just said what the main problem is: ChatGPT is not perfect. Code that isn’t perfect (compiles + has consistent logic) is worthless. If you need a developer to look over it you’ve already lost and it would be faster to have that developer write the code themselves.
Have you ever gotten a pull request with 10k lines of code? The AI could spit out so much code in an instant, no developer would be able to debug this mess or do a code review. They’ll just click “Approve” and throw it on the giant garbage heap whatever the AI decided to spit out.
If there’s a bug down the line (if you even get the whole thing to run), good luck finding it if no one in your developer team even wrote the code in the first place.