The Bun rewrite proves 'never rewrite from scratch' was always a cope
An AI-driven team of 64 agents converted over half a million lines of Zig code to Rust in just 11 days, demonstrating the viability of automated code migration.
- 64 AI agents rewrote 535,000 lines of Zig code to Rust in 11 days, proving large-scale automated code migration is feasible.
- The project challenges the assumption that major rewrites require extensive manual effort and time.
- AI-driven code migration could reduce costs and risks associated with large-scale software modernization.
- This experiment validates the strategy of incremental, AI-assisted rewrites over full-from-scratch overhauls.
A team of 64 AI agents completed a full rewrite of 535,000 lines of Zig code to Rust in just 11 days, showcasing the potential of AI-driven code migration at scale. The project, led by a developer known as Adi Iofin, leveraged autonomous agents to handle the complex task of translating syntax, resolving dependencies, and ensuring functional equivalence between the two languages. This achievement challenges the conventional wisdom that large-scale rewrites require extensive manual effort and significant time investment.
The success of this experiment suggests that AI agents can now reliably automate parts of the software development lifecycle that were previously considered too complex or risky for automation. While the original Bun project (a JavaScript runtime) was rewritten from scratch in Rust, this new approach demonstrates that AI can handle such migrations without starting from zero, validating the idea that 'never rewrite from scratch' may no longer be a coping mechanism but a practical strategy.
Demonstrates that AI can handle complex, large-scale code migrations, reducing manual workload.
Offers a path to modernize legacy systems faster and with lower risk.
Shows AI's growing role in automating traditionally human-intensive software tasks.
- Zig
- A systems programming language designed for robustness, optimality, and clarity.
- Rust
- A systems programming language focused on performance, safety, and concurrency.
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