Every agent I've seen in Go has been so straightforward. Take exe.dev's Shelley. Great example of clean code and very effective tooling. Worth a try if you haven't used it.

As long as python runs all the models, the best language for agents is likely Python as it allows e.g. auto-fine-tuning of (local) LLMs for self-improving agents without the need to change the programming language. Use Pydantic if you care about type/runtime errors.

i have not used go for a while until claude code 4.5+, and yes it's the best language for AI coders.

I wonder how many tokens are spent generating: if err != nil {return err} for large programs and over a long period of time.

May be this is good incentive to improve error handling in Go.

I had a lot of success when having agents write D code. The results for me have been better than with C# or C++. I hadn't considered Go. Does anybody have some experience about how D fares vs. Go?

> Joy and energy is one of the rarest resources a small team can have when building large projects

I really love this point-out. Not always an easy sell upstream, but a big factor in happy + productive teams.

Static compiling is a minus not a plus. Dynamic languages like Clojure allow agents to REPL and prod with the code live, and follow Verified Spec-Driven development a whole lot better. Lisp-like languages allow agents to create the exact data structure they need for every problem.

I find typescript pretty useful. As others pointed out the stricter the compile stage is, the better.

On the other hands if there good conventions it’s also a benefit, for example Ruby on Rails.

Java with orm might be easier actually. Also that middleware for microservices might be overkill (context filling)