zlacker

>>simonw+(OP)
I wonder if the era of dynamic programming languages is over. Python/JS/Ruby/etc. were good tradeoffs when developer time mattered. But now that most code is written by LLMs, it's as "hard" for the LLM to write Python as it is to write Rust/Go (assuming enough training data on the language ofc; LLMs still can't write Gleam/Janet/CommonLisp/etc.).

Esp. with Go's quick compile time, I can see myself using it more and more even in my one-off scripts that would have used Python/Bash otherwise. Plus, I get a binary that I can port to other systems w/o problem.

Compiled is back?

>>behnam+sj
I have certainly become Go-curious thanks to coding agents - I have a medium sized side-project in progress using Go at the moment and it's been surprisingly smooth sailing considering I hardly know the language.

The Go standard library is a particularly good fit for building network services and web proxies, which fits this project perfectly.

>>simonw+eo
It's funny seeing you say that, because I've had an entire arc of despising the design of, and peremptorily refusing to use, Go, to really enjoying it, thanks to AI coding agents being able to take care of the boilerplate for me.

It turns out that verbosity isn't really a problem when LLMs are the one writing the code based on more high level markdown specs (describing logic, architecture, algorithms, concurrency, etc), and Go's extreme simplicity, small range of language constructs, and explicitness (especially in error handling and control flow) make it much easier to quickly and accurately review agent code.

It also means that Go's incredible (IMO) runtime, toolchain, and standard library are no longer marred by the boilerplate either, and I can begin to really appreciate their brilliance. It has me really reconsidering a lot of what I believed about language design.

>>logicp+St
God you people are so lazy.

>>vips7L+wu1
Unnecessarily doing extra work is not a virtue. Leave the Catholicism behind. I'm not using AI to replace proglem solving, thinking through and understanding the problem and then figuring out how to fix it, the systems thinking, design, architecture, algorithms, domain modelling, etc. I'm just not dealing with the BS "what was the order of the arguments this function took again? What's the library API for this?" stuff and writing boiler-plate or managing typechecker-driven refactors. The question is whether what you make is any good, and I still spend a lot of time making sure what I built made sense, is well factored and DRY, and is as elegant as I know how to make it. In fact, with the increased leverage LLMs give me, I've found myself spending more time on code quality and testing than I used to!