I Replaced My Meeting Notes With AI Transcription — Here’s What Actually Works (and What Didn’t)

I used to finish a meeting feeling productive… and then lose another 30 minutes rebuilding what just happened. My notes were always the same story: half sentences, missing action owners, zero context for “we decided X”, and that one moment I needed to remember—gone. So I replaced my meeting notes workflow with AI transcription. Now, most meetings turn into a usable transcript in a few minutes , and I spend about 5 minutes doing a quick human pass (titles, action items, key decisions). It’s not perfect, but it’s consistent—and it saves me 2+ hours per week . This post is a builder story + a practical guide: why built-in speech recognition didn’t cut it, what I tested, what actually improves accuracy, and how I shipped a transcription workflow using the Whisper API (without building a giant infra project). If you want to try the same workflow: Real-time dictation: /speech-to-text Upload a recording: /audio-to-text 1) Why built-in speech recognition wasn’t enough I started with the simple