CLI

CLI stands for command-line interface. Instead of buttons and menus, you type commands into a terminal (the text window developers use to control their computer directly). It has been part of software development forever, but it gained new relevance in the AI era because the most powerful agentic coding tools, including Claude Code, Gemini CLI, and Codex CLI, run natively from the terminal rather than inside a graphical editor.

Why the CLI specifically? Terminal-based AI tools can see your working directory, read your files, run commands, check exit codes, and chain operations in ways that a browser-based AI assistant cannot. They operate where the work actually happens. When an AI coding agent runs in the CLI, it can read your entire codebase, execute shell commands (instructions you type to control your system), manage version control with git, and iterate on results, all without you switching tabs or copy-pasting between windows. That focus is the main reason builders who are serious about agentic workflows tend to end up in the terminal.

The current CLI landscape for AI builders has two broad modes. Scripting assistants translate plain-language requests into shell commands, useful for automating repetitive tasks without memorizing exact syntax. Agentic coding CLIs go further: they plan features, modify multiple files, run tests, and interact with git across an entire session, behaving more like a capable collaborator than an autocomplete tool. Tools like Claude Code, Gemini CLI, Codex CLI, Aider, and OpenCode all fall into this second category, and they differ mainly on model choice, context window size, pricing, and how much autonomy they exercise before asking for approval.