● Covered by 1 source · 1 reportLow impact1 negative
DHH's Campfire rewrites to Rust, Elixir, and Go highlight AI agent limitations
Key points
- DHH commissioned AI-driven rewrites of Campfire from Rails to Rust, Elixir, and Go.
- The Rust rewrite dropped CSRF tokens and replaced Redis with in-process queues.
- The Elixir rewrite had a single process for SQL queries, impacting performance.
- The project highlights the need for precise prompts and human review when using AI for code generation.
AI-Assisted Rewrites of Campfire
David Heinemeier Hansson (DHH), creator of Ruby on Rails, initiated a project to rewrite his Campfire application. The original application, built with Ruby on Rails, was re-implemented in Rust, Elixir, and Go. These rewrites were reportedly performed by a 'clanker' (an AI agent) based on DHH's requests.
Functional Differences and Compatibility Issues
Analysis of the rewritten code reveals significant functional differences across versions. The Rust rewrite, for instance, did not maintain 100% backward compatibility, notably dropping CSRF tokens to simplify caching and replacing Redis with in-process queues for notifications. In contrast, the Elixir rewrite was closer to the original Rails version in terms of compatibility. These variations indicate that AI agents make implicit design decisions when prompts lack specific instructions regarding compatibility, performance, and system constraints.
Performance and Design Flaws
Beyond compatibility, the rewrites also exhibited performance and design issues. The Elixir version, for example, was observed to process all SQL queries sequentially within a single process, even for read operations that could run concurrently. This design choice negatively impacts performance and suggests that AI-generated code may not always produce optimal or performant solutions without explicit guidance and human review.
Implications for AI in Software Development
The Campfire rewrite project serves as a case study on the current limitations of using AI agents for complex software development tasks. It underscores the necessity for developers to provide highly specific prompts, define non-functional requirements clearly, and critically review AI-generated code. Relying solely on AI without human oversight can lead to unintended architectural decisions, compatibility breaks, and performance bottlenecks, emphasizing that human thought and code review remain essential.
✨ This summary was generated by AI from the outlets' reporting listed below. It is not independently verified and may contain errors — check the original sources. How BrevFeed works →
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Reporting from
David Heinemeier Hansson (DHH) commissioned rewrites of his Campfire application from Ruby on Rails to Rust, Elixir, and Go using AI agents. The resulting code, particularly the Rust version, introduced functional differences and performance issues, demonstrating that AI agents require specific prompts and human oversight to avoid unintended design choices and maintain compatibility.