From a Question at the Mac to My Own Voice-Input Tool for AI Work

Martin Rau · 12. Juni 2026 · 4 Min. Lesezeit

It started out completely unspectacularly. I was sitting at the Mac and thought to myself, surely there has to be some key I can just press and start speaking, instead of laboriously typing everything out. And it turns out that key exists. On the Mac, dictation is built right in — you just have to find it and switch it on. That’s exactly what I did, and then I used it for quite a while.

The built-in solution was there — but it never felt good

I never really got happy with it, though. The result was usually imprecise and inaccurate, whole half-sentences ended up garbled in the text, and every single time there was that annoying confirmation chime on top. It just didn’t feel good. I stuck with it for a while anyway, because the basic idea wouldn’t let go of me. Speaking instead of typing felt like the right direction, even if the execution was still bumpy.

The detour via ChatGPT

Speech recognition in Claude had been fairly weak for a long time anyway. In English it was passable, but in German it didn’t convince me at all. And that’s exactly where ChatGPT was always genuinely strong. Its German speech recognition was on a completely different level from the start, and I’d been working with it for a long time already. It simply worked reliably, and reliability was exactly what I was after.

Out of that grew a working style that, looking back, seems almost a little absurd. Over time I was working more and more with Opus — that is, with Claude — but at the same time I didn’t want to give up ChatGPT’s good speech recognition. So I always had a little extra ChatGPT window open, purely for recording my voice. I’d speak into it, copy out the finished text, and paste it back over in Claude. Back and forth, window by window.

That sounds cumbersome, and strictly speaking it was. In practice, though, it was still much faster than typing everything myself. Each time it was a small, almost funny moment, because I’d think to myself that surely nobody should actually be working like this.

The moment it clicked

And it was exactly in that moment that it became clear to me: this is actually a really good way to work. Definitely faster than typing — no question about it. The only thing I wondered was why nobody had poured this cleanly into a tool that connects both sides — good speech recognition on one side, working with Claude on the other.

That’s precisely where the idea came from that I’d have to build it myself. If there’s no tool that brings good speech recognition and working with Claude under one roof, then I’ll just build it myself. And that’s how, step by step, I slid deeper into the topic.

From workaround to my own tool

At first it was just the basic idea: to make this speaking-instead-of-typing properly usable. Then it moved toward the command line, because I noticed that’s where I can squeeze out the most control and speed. And finally the most exciting question of all came into play, namely how to optimize the whole thing and which models are best at turning speech into text.

That’s exactly where I’m testing right now. I’m trying different variants — once with a key press and once entirely without, meaning whether I actively start the recording or whether it just runs along in the background. On top of that, I’m comparing different models to see which one turns speech into text most accurately and most quickly, especially in German.

What it's really about

A simple question at the Mac turned into a tool of my own that I keep refining. Not because I was desperate to build something — but because the missing clean solution kept catching my eye in everyday work.

Conclusion

That’s where things stand right now. Looking back, what I like most about this story is that it didn’t start with a grand plan, but with a small, almost naive question at the Mac. Those questions are often the best starting points: you stumble over something that’s cumbersome, find a bumpy detour, and at some point you realize the detour is actually the better path — it just hasn’t been built cleanly yet. This is part one; the next parts will be about the model comparison and how the tool is actually put together.

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