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I use Claude Code and Codex constantly, and my workflow was always the same: launch the agent, need a shell in the same directory, open a new tab, cd back.
Fifty times a day. So I built auto-snap into Yaw — launch any AI coding CLI and it detects it and splits the pane automatically. Agent on the left, fresh shell in the same directory on the right. Works with Claude Code, Codex, Gemini CLI, and Vibe CLI. You can install any of them through a built-in wizard. Yaw is also a full terminal (tabs, split panes, broadcast, search, session restore, WebGL via xterm.js) with a built-in connection manager for SSH, PostgreSQL, MySQL, SQL Server, MongoDB, and Redis — encrypted credentials, Tailscale auto-detection, remote Screen session management. And a chat panel that sends terminal output as context to Claude, ChatGPT, Gemini, Ollama, and six other providers. Electron + xterm.js + React. v0.9.75, Windows and macOS. Curious what other people's AI coding CLI setups look like — what's working, what's missing? |
What's interesting about the AI coding CLI workflow space is that the tooling is evolving much faster than the mental models for using it well. The terminal is becoming a coordination surface — not just for running commands, but for managing the relationship between human attention and agent execution.
The Agile Vibe Coding Manifesto's concern with "automation remaining verifiable" is partly a terminal/observability problem: when the agent is running in a pane you can see, its actions are visible and interruptible. When it's a background process with only a text log, the accountability relationship degrades.
Curious how the chat panel that sends terminal output as context to the AI compares to just having the agent run in a pane you can see — that seems like the interesting design tension here: https://agilevibecoding.org