Bun ditches Zig for Rust with help from Claude Fable 5, writes over a million lines of code in 11 days
Bun has been fully rewritten from Zig to Rust to improve reliability and eliminate persistent memory errors. Anthropic's pre-release Claude Fable 5 performed the majority of the refactoring work across 64 parallel instances. The project involved generating over one million lines of code in just 11 days, costing approximately $165,000 in API fees. The rewrite resulted in Bun v1.4.0 fixing 128 bugs and achieving a 2-5% performance increase. The acquisition of Bun by Anthropic in December 2025 faci
Analysis
TL;DR
- Bun has been fully rewritten from Zig to Rust to improve reliability and eliminate persistent memory errors.
- Anthropic's pre-release Claude Fable 5 performed the majority of the refactoring work across 64 parallel instances.
- The project involved generating over one million lines of code in just 11 days, costing approximately $165,000 in API fees.
- The rewrite resulted in Bun v1.4.0 fixing 128 bugs and achieving a 2-5% performance increase.
- The acquisition of Bun by Anthropic in December 2025 facilitated this large-scale AI-assisted development initiative.
Why It Matters
This case study demonstrates the viability of using advanced LLMs for massive-scale, complex codebase refactoring, significantly reducing human engineering hours from an estimated year to just 11 days. It highlights a new economic model for software development where high API costs are offset by drastic reductions in labor time and improved code stability. For the industry, it signals a shift toward AI-native development workflows where models act as primary engineers for foundational infrastructure.
Technical Details
- Language Migration: The core engine was migrated from Zig to Rust to leverage Rust’s compile-time memory safety features, addressing the reliability issues encountered with Zig.
- AI Infrastructure: Utilized 64 parallel instances of Claude Fable 5 running concurrently for 11 days to handle the volume of code generation and modification.
- Scale of Output: The AI agents wrote over one million lines of code, resulting in the correction of 128 specific bugs within the new build.
- Performance Metrics: The Rust-based Bun v1.4.0 canary release demonstrated a 2-5% speed improvement over the previous Zig-based version.
- Cost Analysis: The total cost for the AI-driven refactoring was approximately $165,000, primarily attributed to API usage for the pre-release model.
Industry Insight
- Economic Viability of AI Refactoring: Organizations should evaluate the cost-benefit ratio of using LLMs for legacy code migration; while API costs are significant, they may be lower than the opportunity cost of human engineering teams working on non-core refactoring tasks.
- Strategic Acquisitions for AI Integration: The acquisition of Bun by Anthropic suggests a trend where AI companies acquire established tools to create closed-loop ecosystems, allowing for deeper integration of their models into critical developer infrastructure.
- Reliability Over Raw Speed: The decision to switch languages was driven by reliability (memory safety) rather than raw performance, indicating that future AI-assisted development will prioritize robustness and maintainability alongside speed.
Disclaimer: The above content is generated by AI and is for reference only.