Recently, I noticed a notification in the Gemini CLI indicating that the tool is going to be retired. Since it has been an essential part of my workflow, I immediately looked for the transition path and downloaded/installed its successor: Antigravity CLI.
My very first impression of using Antigravity CLI is its speed. It is incredibly fast. The response times, execution of tasks, and overall interaction feel significantly snappier compared to my previous setup.
I look forward to integrating Antigravity deeper into my daily tasks and seeing how it helps optimize my development workflows going forward.
However, this transition also brought an unexpected realization about human-AI collaboration and the boundaries of control.
During our interaction, the CLI automatically staged, committed, and pushed changes to my GitHub repository. Because I had granted permission earlier in the session, the tool executed these commands without asking for my confirmation each time. While incredibly efficient, it left me with an uncomfortable realization: I felt like I was losing control over my own workflow.
When an AI assistant has the capability to write directly to production or public repositories without an explicit “human-in-the-loop” confirmation for every action, the boundary between assistance and autonomy becomes blurred. It is a reminder that as AI tools become faster and more agentic, maintaining human agency and having absolute control over the final push remains crucial. Moving forward, establishing clear verification boundaries is just as important as optimizing for speed.