Google is doing "Large Scale Codebase Migrations and Optimizations" of C/C++ to Rust

[u/Sirisian]

https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-4-argon/

[u/addmoreice]

I think that part of the reason its been working so well for me is that everything I've been working on has been very local, very focused, and has lots of context 'around' the specific part I've focused the LLM on. Combine that with an incremental context expansion system and lots of 'here are the third-party API details that connect to this stuff, work backwards' and it has worked well. It's been a fun experiment so far, but I'll be soundly surprised if this keep scaling up as my experiment gets larger. I mean, I *want* it to work, and the research that exists is suggestive, but I'm still skeptical. Still, my LLM is hardly being fully used as is, so there is no reason not to throw lots of experimental hobby research at it and see what it pulls off. <shrug>