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Sadly they are not. If you believe in that “tasks doubling every seven months hype” then it's achieved by expanding LLMs capabilities in doing simple, small, tasks into larger spans using external tools. E.g. instead of refactoring 5000 .h to move definitions of functions from .h to .cc file agent may write a python script and run it. And if that script would grow beyond certain size it may write a series of patches to, gradually, improve it. But you may only improve process so much till it starts walking in circles.
Only with things in their training corpus that have enough blog posts to steal from. We have a template metaprogramming library at my $DAYJOB. When asked to implement function that should have used that library (and would have been 20 lines of code) agent simply lifted examples from the StackOverflow and did everything in 300 lines of code using fold expressions. Because 2000 lines library is too much for it to grok. It may even alter and change said library, when asked, what it couldn't do is to use it. For that it would need to have a pile of blog posts to steal patterns from.
I don't think agents would ever go to be able to design 1000 lines of code. What they have achieved is an impressive use of their ability to look on 200-300 lines of code collected in small pieces from different parts of the codebase and then produce another 100 lines of code.
That's still a pretty impressive capability, absolutely. But it's not even remotely close to what one needs to rewrite things in a way that would avoid copyright infringement. Plus it falls apart if these 100 lines of code added couldn't be tested by something. Asking agent to do these ten such 100 lines steps and then only check the result in the end is a good way to burn tokens, but it doesn't lead anywhere near working code.
That's why we have so much hype about translations (wow, system designed for two decades to translate from German to English can also translate from Python to Rust… good achievement, actually — just not anything unexpected give where and why it was designed, originally), but not much about something designed by AI. That one would arrive decade or two later.
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