Basis

Basis is a research organization working on AI agents and core technology for programming. Its blog covers technical work on making language models produce software with mathematical guarantees, and this post, “Ship Your Interpreter,” is one example of that direction.

The core of the post is a pipeline in which LLMs write a formal semantics for a small programming language, and Lean, a proof checker, is used to prove that the interpreter follows those rules even after compilation to low-level RISC-V instructions. The authors frame this against the growing ability of LLMs to find and exploit bugs, presenting verified software as a counterweight.

The material suits researchers and engineers interested in formal methods, programming languages, and AI-assisted verification. Readers who want a practical walkthrough of combining LLM-generated specifications with machine-checked proofs will find the approach relevant.

To get the most from it, read the post alongside Basis’s earlier work, such as the JavaScript-to-WebAssembly compiler experiment mentioned in the text, to see how the verification goal evolved. The post is a research report, not a tutorial or product announcement.

Overall, it is a concise look at how LLMs and proof assistants can be combined to raise confidence in interpreters and compilers.