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An application stack Claude coded directly in LLVM IR

Details

External ID
47354504
Source
HN
Company
—
Product
An application stack Claude coded directly in LLVM IR
Website domain
github.com
Launched
March 12, 2026
Cohort
—
Upvotes
10
Upvotes percentile
0.5781057810578106
Tags
—
Fetched at
Sept. 7, 2026, 9:26 p.m.
Updated at
Sept. 7, 2026, 9:26 p.m.

Description

This repo is the result of a debate about what kind of programming language might be appropriate if humans are no longer the primary authors. Initially the thought was "LLMs can just generate binaries directly" (this was before a more famous person had the same idea). But that on reflection seems like a bad approach because languages exist to capture program semantics that are elided by translation to machine code. The next step was to wonder if an existing "machine readable" program representation can be the target for LLM code generation. It turns out yes. This project is the result of asking Claude to create an application stack entirely coded in LLVM's intermediate representation language.

Enrichment

Theme
Claude integrations and coding agents
Vertical
Horizontal
Function
Dev tools
Audience
Developer
AI stance
AI feature
Project type
Hobby / open-source project
Normalized one-liner
application stack written in llvm ir by claude
Manually corrected
False

Could you build this?

Partial Generating raw LLVM intermediate representation (IR) to assemble a full web or application stack requires deep compiler engineering knowledge to validate, debug, and link correctly against libc/system calls.

What it would actually take: Constructing an application stack in LLVM IR demands precise manual specification of memory models, calling conventions, SSA form, and direct POSIX system call bindings (or manual linking against libc/musl). Tooling requires Clang/LLVM toolchains (`opt`, `llc`, `llvm-link`) to compile the IR modules into native machine code. Debugging memory errors or undefined behavior in raw IR necessitates advanced knowledge of compiler internals and low-level runtime systems.

Discussion

No comments on this launch.

Competitors

Other products that read as similar to this one — 156 launches clear the similarity bar, closest 8 shown.

Attention rank: #79 of 157 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 131 days after the earliest competitor.

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