jordanhubbard/nanolang
Plenty of people have mused about what a new programming language specifically designed to be used by LLMs might look like. Jordan Hubbard (co-founder of FreeBSD, with serious stints at Apple and NVIDIA) just released exactly that.
A minimal, LLM-friendly programming language with mandatory testing and unambiguous syntax.
NanoLang transpiles to C for native performance while providing a clean, modern syntax optimized for both human readability and AI code generation.
The syntax strikes me as an interesting mix between C, Lisp and Rust.
I decided to see if an LLM could produce working code in it directly, given the necessary context. I started with this MEMORY.md file, which begins:
Purpose: This file is designed specifically for Large Language Model consumption. It contains the essential knowledge needed to generate, debug, and understand NanoLang code. Pair this with
spec.jsonfor complete language coverage.
I ran that using LLM and llm-anthropic like this:
llm -m claude-opus-4.5
-s https://raw.githubusercontent.com/jordanhubbard/nanolang/refs/heads/main/MEMORY.md
'Build me a mandelbrot fractal CLI tool in this language'
> /tmp/fractal.nano
The resulting code… did not compile.
I may have been too optimistic expecting a one-shot working program for a new language like this. So I ran a clone of the actual project, copied in my program and had Claude Code take a look at the failing compiler output.
… and it worked! Claude happily grepped its way through the various examples/ and built me a working program.
Here’s the Claude Code transcript – you can see it reading relevant examples here – and here’s the finished code plus its output.
I’ve suspected for a while that LLMs and coding agents might significantly reduce the friction involved in launching a new language. This result reinforces my opinion.
Via Hacker News
Tags: programming-languages, ai, generative-ai, llms, ai-assisted-programming, llm, coding-agents, claude-code
