testing the gemini cli
I’ve been exploring different ways to integrate AI into my workflow, as you might have read in some of my previous posts. Recently, I got access to the Gemini CLI, a command-line interface for interacting with Google’s Gemini models. It promises to bring the power of AI directly to the terminal, which, as someone who spends a lot of time there, is an intriguing concept. I decided to put it through its paces with a simple, yet meta, task.
This is where the experiment gets fun. I decided to test the Gemini CLI by asking it to write a blog post for me. Specifically, this very blog post. The prompt I gave it was to read all my previous posts, understand their style, and then write a new post about the Gemini CLI, all while admitting that it was generated by the tool itself. It’s a bit like asking a robot to write its own instruction manual while it’s still being assembled.
So, how did it do? You’re reading the result. The process feels like a new form of “rubber ducking,” where explaining the task to the AI helps clarify the goal. It’s not about replacing the thought process, but augmenting it. While I’m not sure I’ll be outsourcing all my writing to an AI anytime soon, it’s a fascinating look at how these tools can act as collaborators. It’s another step in the ongoing conversation between humans and AI, blurring the lines in ways I’m still trying to understand.