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Just use Go. LLMs have seen a ton of it, they write it well, it compiles practically instantly, and it has all the advantages of a typed compiled language. I created a big Python codebase using AI, and the LLM constantly guesses arguments or dictionary formats wrong. Unit tests and stuff like pydantic help, but it's better to avoid that whole class of runtime errors altogether.
Why use Go when you can use Rust?
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Performance? Second only to rust and other lower level langs. Surely you don't need this spelled out for you...
If performance is the main difference, whatever that means, then basically Go should be reserved for when Rust and other lower level langs cannot be used due to some other constraint? Are we mainly talking about performant Web backends? Say I am building some app that I know will be CPU-bound, why choose Go over say... Swift?
Or when performance is the main but not the only difference, and there are many other benefits.
>Say I am building some app that I know will be CPU-bound, why choose Go over say... Swift?
Because unless you're building for macOS/iOS, Swift is really a no-go, with lackluster support for other platforms. Plus slow to build and convoluted.
One obvious reason is Python's extreme readability, it has often been described as being as close to executable pseudo-code as one can get. If you're using an LLM to write code I think the rules would be 1. Use a language you know really well so you can read it easily, and add to it as needed. 2. Use a language that has a large training set so the LLM can be most efficient. 3. Use a language that is easy to read. If…
Python is locally readable. Reasoning about larger systems in Python is where things get really hard, because you have to describe how many small individually readable things interact with each other in a very limited vocabulary.
What language do you feel is easier to reason about in the large?
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Problem with Python and other non-strict typed languages is that if you let an LLM to write some stuff, you cannot truly be confident that nothing has broken. Even if your tests all pass. The LLM could have broken some path that only gets run in production in a very specific case. At least with strongly-typed languages you get a compiler error. In big codebases is non-negotiable
Python has had type hinting for quite a while, and adding validation with mypy/pyright/ty as a step in CLAUDE.md (as well as having it as part of your CI pipeline) can emulate static type checking pretty well.
I am using type hints in Python as much as possible for my hand-coding. And it catches a lot of bugs (especially during code refactoring) that I would not have noticed so easily.
IME very few people think Go is harder than TS or JS - TS is quite complex and JS is a footgun range.
JS got popular for nontechnical reasons and TS is an attempt to make lemonade out of it.
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I think that’s sort of the selling point no? It’s really boring. It has like -10 keywords, compiles insanely fast, and has a concurrency model that’s easy to use and read. LLMs are great at using Go tooling to sanity check along the way. It’s easy to write shitty Go but it’s really pleasant to work with if you find those things compelling.
don't you worry about garbage collection?
Garbage collection is not an issue for 99% of programs. And for those that it is, there are ways to mitigate the issue (e.g. there are extremely high performance trading system written in Java, where every last sub-millisecond counts).
Blanket fear of GC reminds me when new programmers learned about how assembly is lower level and can be faster, and wondered why everything is not written in assembly.
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1. Amount of Rust training data isn’t as much as Go. 2. Golang syntax and style is very verbose yet simple. There’s not as many options nor programming language to domain mapping needed as in Rust. Leads to needing less sophisticated LLM to spit out Golang than Rust successfully and efficiently.
This must really depend on your niche. I assume you do web stuff or something? Good luck finding any golang examples in a lot of other fields. Rust, on the other hand, is taking over the world in systems programming.
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Python is locally readable. Reasoning about larger systems in Python is where things get really hard, because you have to describe how many small individually readable things interact with each other in a very limited vocabulary.
hmm, yeah given LLM's ability to churn out lots of code quickly and be overly verbose in that code that is a potential downside. That it could in a quick one time edit create so much intellectual overhead that Python might be the wrong language to understand what is going on. What language do you feel is easier to reason about in the large?