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.
A case for Go as the best language for AI agents
191–200 of 310 posts
Re: A case for Go as the best language for AI agents
#192I have let Gemini, Claude Code and Codex hallucinate the language they wanted to for a few days. I prompted for "design the language you'd like to program in" and kept prompting "go ahead". Just rescued it from a couple too deep rabbit holes or asked it for some particular examples to stress it a bit. It´s a weird-ass Forth-like but with a strong type system, contracts, native testing, fuzz testing, and a constraint…
Interesting project, but I believe the base assumption is already slightly wrong. Why do we assume that LLMs know what kind of language would benefit them? This information is not knowable without doing proper research, and even if there is some research like that, it would have to be a part of the training data. Otherwise it's just hallucination.
I agree, it´s mostly a silly whim taken too far. Too much time in my hands.
In particular the whole stack based thing looks questionable.
In fact the very first answer by Gemini proposed an APL-like encoding of the primitives for token saving, but when I started the implementation Claude Code pushed back on that, saying it would need to keep some sane semantics around the keywords to be able to understand the programs.
The very strict verification story seems more plausible, tracks with the rest of the comments here.
What has surprised me is that the language works at all, adding todo items to a web app written in a week old language felt a bit eery.
Re: A case for Go as the best language for AI agents
#193I've been saying this for maybe nine months vis-à-vis my consulting work keeps proving it. Go is an excellent language for LLM code generation. There exists a large stable training corpus, one way to write it, one build system, one formatter, static typing, CSP concurrency that doesn't have C++ footguns. The language hasn't had a breaking version in over a decade. There's minimal framework churn. When I advise teams…
Most of these reasons apply to Java as much, if not more. It's an even more popular language with even more training data and also has a better type system so more validation on LLM output, etc.
I mostly write Go code (and have barely had to write any code myself in the past months), but today I had to do some work in a Java project and Claude Code was a terrible experience.
It really felt like using AI tooling of a year or two ago. It wasn’t understanding my prompts, going on tangents, not following the existing style and idioms. Maybe Claude was hungover or doesn’t like mondays, but the contrast with Go was surprising.
One example is that I wanted to add an extra prometheus metric to keep track of an edge case in some for loop. All it had to do was define a counter and increment it. For some reason it would define the counter the line before increment it, instead of defining it next to the other counters outside of the for loop. Technically not wrong (defining a counter is idempotent), but who does that? Especially when the other counters are defined elsewhere in the same function?
Anyway, n=1 but I feel it has an easier time with Go.
Re: A case for Go as the best language for AI agents
#194I happen to just stumble across this article https://felixbarbalet.com/simple-made-inevitable-the-economi... extolling the virtues of Clojure. It specifically calls out Go for not being simple in the ways that matter for LLMs. I've no idea myself, I just thought it was interesting for comparison.
Is this your alt account? https://news.ycombinator.com/item?id=47222705 Edit: cool article, I have myself speculated that we will get a new language made for/by llms that will be torture writing by hand/ide but easy to read/follow/navigate/check for a human and super easy for Llms to develop and maintain.
Yes, I really wanted to post the comment and I (wrongly) thought this post got blocked by my procrastination setting. Apologies for the noise.
Re: A case for Go as the best language for AI agents
#195I've been saying this for maybe nine months vis-à-vis my consulting work keeps proving it. Go is an excellent language for LLM code generation. There exists a large stable training corpus, one way to write it, one build system, one formatter, static typing, CSP concurrency that doesn't have C++ footguns. The language hasn't had a breaking version in over a decade. There's minimal framework churn. When I advise teams…
Most of these reasons apply to Java as much, if not more. It's an even more popular language with even more training data and also has a better type system so more validation on LLM output, etc.
Exactly, the propping up of Go seems unfounded. Java in it's newest iterations make it more compelling as a target, and people, especially young people, overlook it because of its stigma as enterprise cruft.
Re: A case for Go as the best language for AI agents
#196This is a great article, thank you for sharing. The 4 languages I've honed in on with respect to AI agents are Rust, Python, C, and Go. Python has a foothold in the tooling for creating AI based on the training of large language models with frameworks including PyTorch and Tensorflow. As long as Python is the language to create AI, it will also be a great language for AI to code in.
The most important downside of Python is that it doesn't compile to a native binary that the OS can recognize and it's much slower. However, it's a great "glue" for different binaries or languages like Rust and Go.
Rust is the increasingly popular language for AI agents to choose from, often integrated into Python code. The trend is on the side of Rust here. I don't want to mention all the great points from the original poster. One technical point that wasn't mentioned, from my experience, is that the install size is too large for embedded systems. As the article mentioned, the build times are also longer than Go and this is an even worse bottleneck on embedded systems. I prefer Go over Rust in my research and development but I yield to other developers on the team professionally.
What about C/C++? At the moment, I've had great success with implementing C++ code through Agentic AI. However, there are a dearth of frameworks for things like web development. Because Python compiles to C, and integrating C modules into Python is relatively straightforward, I find myself implementing the Numpy approach where C is the backbone of performance critical features.
Personally, I still actively utilize code I've written more than 10 years ago that's battle tested, peer reviewed, and production ready. The above comments are for the current state, but what about the future? Another point that wasn't mentioned was the software license from Go. It's BSD3 with a patent grant which is more permissive than Rust's MIT + Apache 2.0 licenses. This is very important to understand the future viability of software because given enough time and all other things the same, more permissive software will win out in adoption.
The rabbit hole goes deeper. I think we will sacrifice Rust as the "good-enough" programming language to spoil the ecosystem with Agentic AI before its redemption arc. Only time will tell, but Python's inability to compile to a native binary makes it a bad choice for malware developers. You can fill in the blank here. Perhaps the stage has already been set, and it looks like Rust will be the opening act now that the lights are on.
Re: A case for Go as the best language for AI agents
#197I think the more you can shift to compile time the better when it comes to agents. Go is therefore 'ok', but the type system isn't as useful as other options. I would say Rust is quite good for just letting something churn through compiler errors until it works, and then you're unlikely to get runtime errors. I haven't tried Haskell, but I assume that's even better.
I wonder if then Idris would be even better than that since it has even more typing
Re: A case for Go as the best language for AI agents
#198Earlier quoted context omitted.
Most of these reasons apply to Java as much, if not more. It's an even more popular language with even more training data and also has a better type system so more validation on LLM output, etc.
I mostly write Go code (and have barely had to write any code myself in the past months), but today I had to do some work in a Java project and Claude Code was a terrible experience. It really felt like using AI tooling of a year or two ago. It wasn’t understanding my prompts, going on tangents, not following the existing style and idioms. Maybe Claude was hungover or doesn’t like mondays, but the contrast with Go wa…
Well, there was a Claude outage today, maybe related :D
My n=1 is that it is pretty good with Java, on par with other popular languages like Python and JS, in line with these 3 probably being a good chunk if not the majority of training data.
Re: A case for Go as the best language for AI agents
#199Earlier quoted context omitted.
Java has decade(s) of cruft and breaking changes which LLMs were trained on. It's hard to compare. Plus Go compilation speed/test running provides quick iteration for LLMs.
breaking changes? hardly.
There is a decently long list of breaking changes now. Removing JavaEE modules from the JDK, and restricting sun.misc.Unsafe, are the ones people usually run into.
Re: A case for Go as the best language for AI agents
#200Have yet to find a better choice than OCaml: - Strongly typed, including GADTs and various flavors of polymorphism, but not as inscrutable as Haskell - (Mostly) pure functions, but multiple imperative/OO escape hatches - The base language is surprisingly simple - Very fast to build/test (the bytecode target, at least) - Can target WASM/JS - All code in a file is always evaluated in order, which means it has to be def…
Strong agree. OCaml's compiler is sofa king good at catching and preventing real bugs that the agents accidentally introduce here and there. It's the same as with humans, except the agents don't complain about the bullshit reasons humans don't like OCaml. They just crank through and produce high quality output.