We tasked Opus 4.6 using agent teams to build a C Compiler (www.anthropic.com)

A new approach called "agent teams" has been developed using multiple instances of the Claude language model to autonomously work on software projects, significantly enhancing the capabilities of AI in code generation tasks. In a recent experiment, 16 agents were tasked with building a Rust-based C compiler capable of compiling the Linux kernel. Over the course of nearly 2,000 sessions and close to $20,000 in API costs, they managed to produce a 100,000-line compiler that successfully compiles Linux 6.9 across various architectures like x86, ARM, and RISC-V. This project showcases the potential of AI in automating complex programming tasks without human oversight, indicating a promising future for AI-driven software development. Key technical innovations include a robust harness design that allows agents to operate in a continuous loop, enhancing their ability to tackle long-term projects without frequent human input. The arrangement fosters specialization among agents, so some could focus on code quality while others worked on documentation or specific tasks, minimizing overlap. The results demonstrate that while the AI-generated compiler achieves impressive feats, it also highlights areas for improvement—most notably in code efficiency and quality, indicating that while AI can create functional code, human expertise remains essential for more sophisticated programming challenges.