A developer with eight years of Go experience argues that Go is the optimal language for AI agent coding. The author, who built Bruin - an open-source ETL tool - initially faced the decision of whether to use Go or Python for their CLI tool. Python offered more libraries and developers, but Go's compilation speed and simplicity ultimately won out.

Several key factors influenced this decision: Go's concurrency model suited data orchestration needs, its ecosystem provided decent API integration, and the language's speed was crucial for CLI tools that might serve as VS Code extensions or local UIs. The author also valued Go's predictable error handling and cross-platform support, which was essential for software running on users' machines. Most importantly, the developer enjoyed working with Go, which proved vital for maintaining motivation on large projects.

Go's compilation creates a fast feedback loop for AI agents, catching type errors before runtime. The language's simplicity makes generated code readable and maintainable, while its opinionated standards ensure consistency across projects. Cross-platform binary building is trivial in Go, allowing agents to validate their work across environments quickly. These advantages position Go as the superior choice for AI-assisted development, combining speed, reliability, and developer satisfaction.