yeah i love that there is a lot of source data for "what is good idiomatic go" - the model doesn't have it all in the training set but you can easily collect coding standards for go with deep research or something

And then I find models try to write scripts/manual workflows for testing, but Go is REALLY good for doing what you might do in a bash script, and so you can steer the model to build its own feedback loop as a harness in go integration tests (we do a lot of this in github.com/humanlayer/humanlayer/tree/main/hld)