Go

Go was designed at Google to be simple, fast, and easy to deploy. It compiles to a single self-contained binary you can drop on a server with no runtime to install. It deliberately leaves out fancy features, which keeps codebases boring in the best way — and boring is easy for both humans and AI to reason about.

• Good at: fast backend services, command-line tools, networking, anything that needs to handle lots of concurrent connections, simple deployment.
• Where it hurts: verbose error handling (you'll see if err != nil everywhere); not a frontend language; the deliberate simplicity can feel limiting if you want expressive shortcuts.
• Typical use cases: APIs, microservices, CLIs (a CLI, or Command-Line Interface, is a text-only way to run programs by typing commands), infrastructure tooling, high-traffic backends.
• AI handling: very good. Go's small, consistent feature set means there's a "right way" to do most things, and assistants follow it well. Less training data than JS/Python, but the simplicity compensates.

Go's killer feature for a solo builder is that single binary. There's no "install Node and these forty packages on the server" dance, no runtime version mismatch between your machine and production. You build, you copy one file, you run it. That alone makes deployment dramatically less error-prone — which matters a lot when you're vibe coding and don't want to debug infrastructure. The verbosity is the cost: code that would be three lines in Python becomes eight in Go. But those extra lines are predictable, and predictable is exactly what an AI handles well.