Anthropic researcher Nicholas Carlini used 16 instances of Claude Opus 4.6 AI model to collaboratively build a C compiler from scratch over two weeks. The AI agents worked autonomously in separate Docker containers, sharing a Git repository and claiming tasks independently without central coordination, at a cost of about $20,000 in API fees. The project resulted in a 100,000-line Rust-based compiler capable of building a bootable Linux 6.9 kernel across multiple architectures (x86, ARM, and RISC-V). The compiler achieved a 99 percent pass rate on industry standard tests and can compile major open source projects including PostgreSQL, SQLite, and Redis.

This experiment demonstrates the potential of multi-agent AI systems to tackle complex software development tasks collaboratively, coinciding with both Anthropic and OpenAI launching multi-agent tools. The project showcases AI's ability to work autonomously on well-defined technical problems with existing specifications and test suites. However, the experiment highlights important limitations of current AI coding capabilities - C compiler development represents an ideal scenario with decades-old specifications, comprehensive existing tests, and reference implementations for validation. Most real-world software projects lack these advantages, and the greater challenge in development typically involves determining requirements and designing appropriate tests rather than writing code to pass existing tests.