AI

I use voice-to-text constantly. I dictate prompts when working with AI, draft longer thoughts when typing feels too slow, and fire off messages to friends without forcing my thumbs through several paragraphs on a phone. The technology for this is not new, but the experience has often felt strangely compromised. Many transcription tools want another subscription. Others send audio to a closed-model API, which introduces a recurring cost and means trusting yet another service with my voice recordings. Even when a product works well, I am usually adapting my workflow to whatever its developers decided to build. Recently, I tried a different approach: I built the version I wanted for myself. It runs locally on my Windows computer, activates from a keyboard shortcut, and all it uses is an NVIDIA RTX 4060 Ti with 8 GB of VRAM – no special Mac M5 chips or top of the line gaming cards. The everyday transcription path is fast enough that I barely think about it. When it makes a mistake, a second shortcut I’ve created reprocesses the saved audio with a more capable model and replaces the original text. This article, fittingly, began as a voice transcription using that system. ...

This article was created and published entirely through an AI agent. It represents a fully automated workflow from creation to deployment on the live website. This demonstrates the power of combining Hugo, automated scripts, and intelligent tooling to streamline the content publishing process. Stay tuned for more articles!