Embracing the parallel coding agent lifestyle
4 days ago
- #parallel programming
- #software development
- #AI coding agents
- Engineers are increasingly using multiple coding agents simultaneously for various tasks.
- Initial skepticism about parallel coding agents due to the bottleneck in reviewing AI-generated code.
- Effective patterns for using parallel agents include research for proof of concepts, understanding existing systems, and handling small maintenance tasks.
- Research tasks help answer questions or provide recommendations without modifying the project.
- Coding agents can build proof of concepts with new libraries, even if they are not in the training data.
- LLMs can provide detailed explanations about existing systems, useful for future reference.
- Small maintenance tasks, like fixing warnings, can be outsourced to coding agents to save time.
- Carefully specified tasks reduce the effort needed to review AI-generated code.
- Current tools include Claude Code, Codex CLI, Codex Cloud, GitHub Copilot Coding Agent, and Google Jules.
- Usage patterns involve multiple terminal windows, Docker containers for safety, and asynchronous agents for riskier tasks.
- GitHub Codespaces is useful for workshops and demos due to its accessibility.
- Encouragement for others to share their effective patterns as the field evolves.