Show HN: Distribute AI agent test runs across your spare machines via `rr` (github.com)

A new tool called `rr` has been launched to streamline the process of running heavy workloads on remote machines. It allows developers to sync their code to a remote host and execute commands with just one simple call, eliminating the need for complex setups with rsync or SSH. With features like smart connection failover, distributed locking, and load balancing, `rr` can run parallel tasks across multiple machines, significantly enhancing efficiency—especially for agentic coding workflows where AI agents frequently run tests to validate their work. This tool is particularly valuable for developers engaged in Test-Driven Development (TDD) with AI coding assistants like Claude Code or Cursor. By distributing test runs across a pool of machines, `rr` prevents conflicts that arise when multiple agents attempt to execute tests simultaneously on a single localhost. Moreover, its user-friendly features such as real-time monitoring and automatic error formatting make it an effective solution for managing extensive testing processes, ultimately leading to a more accelerated feedback loop and increased productivity in AI and machine learning projects.