I’m deeply sceptical. Every time a major announcement comes out saying so-and-so model is now a triple Ph.D programming triathlon winner, I try using it. Every time it’s the same - super fast code generation, until suddenly staggering hallucinations.
If anything the quality has gotten worse, because the models are now so good at lying when they don’t know it’s really hard to review. Is this a safe way to make that syscall? Is the lock structuring here really deadlock safe? The model will tell you with complete confidence its code is perfect, and it’ll either be right or lying, it never says “I don’t know”.
Every time OpenAI or Anthropic or Google announce a “stratospheric leap forward” and I go back and try and find it’s the same, I become more convinced that the lying is structural somehow, that the architecture they have is not fundamentally able to capture “I need to solve the problem
I’m being asked to solve” instead of “I need to produce tokens that are likely to come after these other tokens”.
The tool is incredible, I use it constantly, but only for things where truth is irrelevant, or where I can easily verify the answer. So far I have found programming, other than trivial tasks and greenfield ”write some code that does x”, much faster without LLMs