Nicholas Carlini, a researcher at Anthropic, ran 16 separate Claude Opus 4.6 AI agents on a shared project, instructing them to collaboratively build a C compiler from the ground up. Over the course of two weeks and with a budget of roughly $20,000, these systems generated a large-scale Rust-based compiler able to produce a bootable Linux 6.9 kernel compatible with x86, ARM, and RISC-V hardware, marking a notable milestone for autonomous coding powered by current technology models.
This was the first time an AI language model produced a working, multi-architecture compiler with minimal human involvement and limited funding. The process used multiple parallel agents that worked independently inside Docker environments, coordinated their efforts via Git, and resolved any code conflicts on their own. Their workflow utilized robust engineering methods like smart test integration and strong time control, which could inform wider application in future self-directed software projects.
The task was well suited for AI-driven development because it had clear specifications, extensive automated tests, and pre-existing compilers for comparison. While the finished compiler had some flaws, such as incomplete 16-bit x86 support and issues in assembler and linker code, it still succeeded in compiling the Linux kernel and several major software projects, passing almost all test cases and showing impressive capability with complex programming challenges. Human guidance was limited to setup, requirements, and test validation, and no direct coding or debugging was performed by people.
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