All code has bugs, the vector space of all possible bugs determines the entropy of the problem space for a large language model to traverse.
replyReduce entropy, increase probability of the correct outcome.
LLMs are surfing higher dimensional vector spaces, reduce the vector space, get better results.
Because you'll have to review it, and Go's design limits the number of ways it can go wrong.
replyCode is free, sure, but it's not guaranteed to be correct, and review time is not free.
If code must be correct, and review time is not free, and review time is costlier than code time, why not just ...
reply... write the code yourself?
I 100% agree, and do, but it's an answer to the GP's question (why generated code language matters)
replyI think many many people just skip the "review" step in this process, and assume they're saving time. It's not going to end well.
I thought about this for a while and came to a conclusion that while "code is free", tokens are not. If tokens were free and instant, it would generate machine code directly. Therefore, it needs abstractions like a compiled or interpreted language in order to address the token bottleneck.
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