Working with AI has fundamentally changed what I use a terminal for. I now use it for almost all my work: coding, planning, review and drafting, from start to finish, and when revisiting it later.
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一分鐘完成驗證Essays by Andy Yunxin Wu on the motivations and design choices behind AgentTerm.
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檢視完整 README ↗Working with AI has fundamentally changed what I use a terminal for.
I now use it for almost all my work: coding, planning, review and drafting, from start to finish, and when revisiting it later. My focus is on understanding and steering AI’s work rather than running commands. That calls for fresh designs around this new kind of interaction, both inside the window and across the desktop.
So I have been building AgentTerm since January, and it has changed how I work (demo). These notes share the thinking behind its design.
Agents show up when needed.
Works like an installed app. Personalize it without the friction.
I can edit the rendered content to propose changes; my agent refines it and replies in place.
AgentTerm understands agents; agents understand AgentTerm.
I have been adding capabilities on top of this new terminal.
I removed a check so we focus on what needs my judgment.
AgentTerm annotates transcribed speech, and my agents correct garbled text using the context of our work.
AgentTerm has other features and design choices not covered above, such as commenting on agent output, copying it without reformatting, connecting to an IDE, running long jobs, coordinating a shared workspace, and setting up and invoking guides across AI CLIs using a namespace convention based on folder paths.
Use AgentTerm as is, or adapt it to your work.