Example scenario: you have a codebase that you iterated on with LLM, and it contains let's say 15 features with various implementation details. You continue tomorrow and want to make a small change to handle an edge-case. While making changes to one of the 3 required files, suddenly it will decide to also rewrite / "improve" other parts of the code that have nothing to do with your request, where pieces of previous logic will no longer exist - since it made 18 changes to the file, and there are 3 such files, good luck spotting it without thorough and detailed change review.
Also, if you made manual changes to generated code and than you ask it to add something to the code (within the same "conversation" / context, it will often replace your changes with how it originally wanted code to look like.
I think people will have to recalibrate on this. The LOCs do things that you otherwise would not do. Features and details that simply would not happen — because they are too code/time intensive for most projects. It just won't matter anymore.
> But why would non-technical people would even think in terms of log tailing and version control
They won't! They won't have to. The obvious good stuff, that everyone thinks the AI tool should be able do, will just work, because the people building the tools, will focus on making them work.
I can't really imagine producing that much code in that short amount of time and holding any amount of it in my head. I'd bet money there's code in there that does the same thing but different, leading to all kinds of little inconsistencies that make this code worthless in any serious context.
I have entire codebases of embedded software in C without the shortcuts of modern programming languages in way fewer than 35k lines
Not 35k lines, but there's one line that's about 48,000 characters long. So either they've intentionally obfuscated it, or chatgpt just churned out one long line
Edit: Running it through a prettifier the code comes about 33k lines
Edit: Run it through another prettifier, might turn into 35k lines. :D
35 kLOC is quite a bit. I wonder how straightforward and maintainable this app ended up to be. This would require taking a look at the sources. While good Rails code tends to be very terse, frontend may be quite voluminous.
> I believe within a couple of months, when things like log tailing and automated testing and native version control get implemented
This sounds a bit too optimistic, especially around automated testing, but yes, eventually this all will be there.
> an extremely powerful tool for even non-technical people to write production-quality apps
But why would non-technical people would even think in terms of log tailing and version control, any more than they think about the gauge of wiring in their walls, or the kind of modulation their Wi-Fi device use? For really non-technical audience to make a good use of such tools, it won't just take the AI to be a competent coder. The AI should become a competent architect and a competent senior SWE to translate from the product management language to the software development language, without even surfacing it when not explicitly asked. It's going to be quite a bit of a challenge to make it work, and work about as reliably as with a human team.