alt Hacker NewsI'm not sure I trust a source that says "just 70 tokens average, nearly half of Clojure (109 tokens)".
There's no reason to add the phrase "nearly half of", and there's especially no reason to add it when it's significantly far away from half.
But on the main topic, I still feel that Go is an excellent choice for LLMs. There is pretty much just one way of doing most things, and the available training data is pretty consistent. This is very different from Python, where training data is polluted (I presume) with tons of code written by non-software engineers and demonstrating many different ways of doing the same thing.
Also a big plus for Go is the tooling. Fast compiles and good linting shortens the iteration cycle time, resulting in less need for me to tell the LLM to correct mistakes.
For some reason, most LLMs I've used default to wanting to write Python. I have to repeatedly teach them to use Go unless there is a very compelling reason to choose otherwise.
I would personally rather see and use Clojure, but I don't feel its ecosystem would provide the same benefits as Go, including obviously the easy single binary distribution.
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Professionally, Scala was always my favorite language to work in and I was lucky to get to use it most of my career. It is, however, probably the worst language I’ve experienced using with LLMs. Next worst is any dynamic language: it’s just so hard to not introduce strange bugs after iterating on a large-ish project across multiple agent sessions.
I’ve had good enough experiences with Rust, but actually OCaml has been hands down the language I’ve seen best results with. The quality (and performance) of code is just phenomenal — and the main issue when working as a solo human with the language, namely smaller pool of community libraries, just isn’t an issue any more. Jane Street has really done tremendous work modernizing the language and tooling.
I like Go with agents too but:
> This is very different from Python, where training data is polluted (I presume) with tons of code written by non-software engineers and demonstrating many different ways of doing the same thing.
Counter-example: agents with Django-related stuff. Excellent output.
Agree that go is the best due to its main design goal: A language that's simple for any programmer fitting that definition https://news.ycombinator.com/item?id=30688969.
> "They’re not capable of understanding a brilliant language but we want to use them to build good software. So, the language that we give them has to be easy for them to understand and easy to adopt."
This makes it a great language not just for young Googlers programmers, but also for LLM Agents!
IMO, the next big language will be similar philosophy, but without garbage collection. (is Zig the closest to filling that niche?)
I’ve gone down the same logical pattern of using Go for llms even though I personally prefer Clojure.
You can rather easily ship Clojure apps as single binaries, eg with this: https://github.com/avelino/jbundle
> This is very different from Python, where training data is polluted (I presume) with tons of code written by non-software engineers and demonstrating many different ways of doing the same thing.
Python's philosophy is there is one way to do it, as opposed to Perl's TIMTOWTDI.
Your statement also assumes that 'software engineers' write the best code, and from my experience, this is definitely not true
I believe the training data should simply be limited to only code written by someone like Fabrice Ballard, or whoever you think writes the best code.
Go is absolutely one of the best programming languages for LLMs for the reason you say, and Python is just what LLMs like to use to write short throwaway scripts. Frontier LLMs are generally pretty good at most programming languages and can pick up new ones pretty quickly. Training data seems to mostly just increase the speed which they write code, for example, GPTs tend to write Rust and Python faster than other programming languages.
For actual output quality, the main deciding factor is simply how much tooling it is there for the LLMs to check their own work, as LLMs seemed to avoid using a lot of libraries in general. That's why C# is underrated due to the tooling strength of the .NET ecosystem, as long as you tell LLMs to avoid using reflections unless absolutely necessary.
C++ is also surprisingly good, but you pretty much have to tell the LLMs to treat it like Go and don't use any of the dangerous features for normal code.