Using AI slop in software that runs ML models is like buying a Ferrari with a motorbike engine. Might be good for demos or as a proof of concept, but that can’t be used for serving LLMs at scale

At the risk of noting that this is a PR statement from someone who needs something from AMD - you do realize that you just shat upon the CTO of the largest possible consumer of a technology talking about that technology? It's not 2022 anymore.

Just pointing out, there is a reason the large LLMs keep working to try to make it so their own tools can't attack their own moats, by preventing the exact behavior that you dismiss above.

That would be a very defensible take back in year 2023. Now though?

Anthropic has Mythos. That thing's low level code "AI slop" is better than the "meatbag slop" most software developers write, and it can keep cracking at a given problem with persistence.

OpenAI has GPT-5.6, and also that rabid dog of an AI model that was last seen out in the wild tearing HuggingFace open.

Modern LLMs are very, very capable - not just of writing raw code, but also of persistent, methodical problem solving. Which is what you want to tackle things like "port from an exotic system A to an exotic system B and smoke test the port". Persistently hunting for testable optimizations is a good fit too.