claudes-c-compiler

-compiler/issues/74). > which, in comparison with a correct modern C compiler, is far less performance critical, complex, broad, etc. That code might be less complex for us, but more complex for an LLM if it has to deal with lots of domain-specific context and without a test suite that has been developed for 40 years. Also, if the end result of the LLM has the same problem that Anthropic concedes here, which is that the project is so fragile that bug fixes or improvements are really hard/almost impossible, that still matters. > it really seems that the complaints here aren't about the LLMs themselves, or the agents, but about what people/organizations do with them, which is then a complaint about people, but not the technology It's a discussion about what the LLMs can actually do and how people represent those achievements. We're point out that LLMs, without human supervision, generate bad code, code that's hard to change, with modifications specifically made to address failing tests without challenging the underlying assumptions, code that's inconsistent and hard to understand even for the LLMs. But some people are taking whatever the LLM outputs at face value, and then claiming some capabilities of the models that are not really there. They're still not viable for using without human supervision, and because the AI labs are focusing on synthetic benchmarks, they're creating models that are better at pushing through crappy code to achieve a goal.

" in the above link - that's just an ephemeral rootless container instance on a dev VM host from a template named "main" I spun up to mess with CCC. I.e. "don't let the prompt imply I recommend using actual root on your actual main box to do much of anything, let alone run random projects from GitHub" :).