[0] tasks included making games from scratch and resolving bugs we put into template projects. There's no perfect tasks to test on, but this seemed sufficient
Some of the AI generated I've seen has been decent quality, but almost all of it is much more verbose or just greater in quantity than hand written code is/would be. And that's almost always what you don't want for maintenance...
Obviously you cannot generalize that to all software development though.
This is in part because context limits of large code bases and because the knowledge becomes more specialized and the LLM has no training on that kind of code.
But people are making it work, it just isn't as black and white.
I'm currently using AI (Claude Code) to write a new Lojban parser in Haskell from scratch, which is hardly something "super basic and common". It works pretty well in practice, so I don't think that assertion is valid anymore. There are certainly differences between different tasks in terms of what works better with coding agents, but it's not as simple as "super basic".
