This is neat, but, as with all projects in this vein, I fail to see the real value add. We've had ML-powered code generation for several years now (Copilot released publicly in late 2021), and apart from a cute novelty, there's no real use case I've found. (
Maybe except for generating tests, but when dealing with a novel code base, the models really can't figure out dependency injection, mocks, weird edge cases I'd care about, etc.)
This might be a bit contrarian, but I don't really think there's product market fit here, at least for engineers. And if given in the hands of non-engineers, you'll need to have an engineer at least look over the code anyway. I haven't seen or heard of anyone that seriously uses ChatGPT to generate code and uses it in prod (apart from engagement-farming Twitter posts).
> Understanding someone else’s code for large internal engineering teams is often a challenge
Without proper context, this will fail miserably. Have you ever seen a corporate codebase before? It can be the definition of "wtf?" even for a seasoned developer that's been working there for years.
This AI-generated code trend reminds me of the "no-code" fad of the past decade.
This might be a bit contrarian, but I don't really think there's product market fit here, at least for engineers. And if given in the hands of non-engineers, you'll need to have an engineer at least look over the code anyway. I haven't seen or heard of anyone that seriously uses ChatGPT to generate code and uses it in prod (apart from engagement-farming Twitter posts).
> Understanding someone else’s code for large internal engineering teams is often a challenge
Without proper context, this will fail miserably. Have you ever seen a corporate codebase before? It can be the definition of "wtf?" even for a seasoned developer that's been working there for years.
This AI-generated code trend reminds me of the "no-code" fad of the past decade.