Lately I’ve found myself talking to my computer more. Not just when I’m mad at it, but also when I’m writing code using AI-assisted tools like GitHub Copilot or Cline. It’s a shift that happened organically as my role evolves from being the primary “driver” of code to more of a “navigator” who guides the overall direction.
What’s interesting is how this practice can improve communication in both human and machine interactions. When you have to verbalize your intent clearly enough for speech-to-text to understand, you naturally become more precise in your explanations. It’s like the old rubber duck debugging technique, but now your rubber duck can actually respond and help refactor your code.
There’s also a physical benefit that I can’t ignore. As someone who has spent countless hours hunched over a keyboard like Gollum with his precious – slowly de-evolving, watching my hands morph into claws – this alternative feels like discovering a cheat code for programmer ergonomics.
It’s not perfect. There’s still plenty of situations where I need to take the wheel, due to both limitations of speech-to-text interfaces and the ability of intelligent coding tools to carry out instructions. But I can definitely feel the difference, even if its not something I can do all the time.
Going beyond the physical benefits, the real value might be in how it changes the way we think about programming interfaces. We’re moving from an era where we had to speak the computer’s language precisely, to one where we can express our intent more naturally. Computers are becoming better at understanding us, rather than the other way around. It’s another small step toward that Star Trek future where we can just say “Computer, refactor this method to use the Strategy pattern” and actually get meaningful results.
Of course, your mileage may vary depending on your environment and tolerance for looking like you’re talking to yourself. But in a world where many of us already spend our days talking to screens, maybe that’s less of a concern.
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