You're 40 minutes into a design doc at 11pm. The payment settlement flow is finally clear in your head, the logic feels tight, and you're speaking it out faster than you could type it. Then the tool stops listening. Word cap hit.
The workflow actually changed
Developer work used to center on typing: writing code, comments, commit messages, all at the keyboard. Voice dictation was a nice-to-have productivity trick, shaving minutes off the typing phase.
Then the LLM shifted the workload. Now half your day is writing intent for models: detailed system prompts, specifications, PR descriptions that explain the why behind a change, design docs that sketch an architecture before you code it. These aren't short thoughts. They're long-form, exploratory, full of clarifications and edge cases that emerge while you're speaking them out.
Voice makes sense for this work. You can't type 2000 words of exploratory thinking faster than you can speak it. But a word cap mid-flow kills the momentum.
Where cloud tools lose
Cloud-based speech-to-text services work fine for transcribing meetings or quick voice notes. Wispr Flow charges $14/month with a free tier that's capped. Willow charges $12/month. Superwhisper is $8.49 as a one-time purchase. All of them meter the free tier because they're paying for cloud infrastructure on your behalf.
For a developer writing a long design doc in one voice session, you'll hit that cap. Marcus, a backend engineer at a fintech, runs into this every time he designs at 11pm. A typical design doc for a payment settlement flow ends up being 1200 words or more, more than he can complete in a single cloud-metered voice session before hitting a limit and either fragmenting the work or paying.
He uses Cursor specifically because tab-complete reduces voice rewrites; he refuses cloud transcription because code snippets in a design doc shouldn't leave his device. Wispr's free tier wasn't designed for his workflow.
Local + uncapped changes the game
Recitey runs Whisper, OpenAI's speech-to-text model, locally on your device. No cloud calls. No variable cost. The free tier is uncapped, no word counter, no metering.
The structural difference: speech-to-text is a commodity now. Running Whisper-large-v3 locally costs nothing at scale; the variable cost is near zero. The product pricing isn't about the transcription; it's about the cloud-side rewrite, the polishing layer that cleans rough voice into clean prose. That's what Pro adds. The dictation is free because it should be free.
Your code stays on your device. Latency is instant (no network round-trip). No monthly bill creep as you write more design docs.
What "free" should actually mean
Premium SaaS pricing often reflects distribution cost more than technology cost. Enterprise speech-to-text is genuinely cheap at scale. But companies meter it because that's how SaaS pricing works: you hook the user on a feature, then charge for depth, speed, or volume.
For developers building in Cursor or Claude Code, that's the wrong frame. Local-first tooling has different economics. A tool that runs locally and doesn't leak your context is worth more than one that's "free" but sends your code to a server somewhere. No word limit means you finish the thought, not fragment the work.
The midnight design doc should be finished. The tool shouldn't be the constraint.