The article argues that speaking long, unfiltered “rambles” to an LLM captures your full train of thought and design trade-offs in a way short typed prompts can’t. It offers tips like embracing uncertainties, recording group debates, and voicing emotions to give the model enough context to make decisions that match your priorities. Finally, it shows how to set up a dictation app or transcription pipeline to feed those recordings into your coding agent.

After six months and over 44,000 dictated words with Wispr Flow at 161 wpm, the author tried FluidVoice. It’s an open-source, local Mac app that corrects in real time without an API key and handles slang better. They canceled their paid plan in favor of FluidVoice.