The moment you hit a word limit mid-thought is the moment you lose the thought.
You're explaining the settlement flow at 11pm in a Notion design doc. The words are flowing. You're three minutes in, the code logic is clear in your head, the whole async pattern clicks. Then the dictation stops. "Free tier limit reached." By the time you switch back, the clarity is gone. You've got 1,847 words on the page and a fragmented thought that'll take you 20 minutes to untangle tomorrow morning.
It's not a productivity problem. It's a momentum problem.
The Bottleneck Shifted
The assumption behind most voice tools is that developers still type code. Typing is slow, so voice is the shortcut. But the work changed. In Cursor and Claude Code and GitHub Copilot, you're not typing code anymore, you're typing the intent. The spec. The edge case. The reason this solution matters. More words. More specific. More voice-friendly.
Wispr ($14/month), Willow ($12/month), and Superwhisper ($8.49) all cap the free tier. Two thousand words per month. Fifty words per day if you're drafting daily. That's three Slack messages. One PR description. Half a design doc. The limit doesn't exist to protect the company. It exists to push you to the paid plan.
The infrastructure cost of local speech-to-text is near zero. It's running Whisper on your device, no cloud round trip. The pricing reflects distribution and brand lock-in, not actual tech cost. Recitey runs Whisper locally on your Windows device. No word counter. No metering. No hidden cap that appears the moment your thought gets long. Free tier is the full product; the paid tier is for the cloud rewrite polish, not the dictation gate.
Why Local Matters More Than You Think
The IP concern is real. Marcus, a backend engineer at a Series B fintech in Stockholm, refuses to use cloud dictation for code because the model company's terms are vague about code storage and training. Cloud providers have strong incentives to absorb your data. Local Whisper means the speech never leaves your device. The transcript is yours. The local model isn't trying to build a dataset out of your work.
Latency matters too. Cloud round trips introduce a delay, sometimes one to three seconds depending on load. That delay breaks the cognitive flow. You finish speaking, you wait for the transcription, the moment passes. By the time the words appear, you're already thinking about the next idea, or you've lost the thread of the current one. Local transcription is immediate. You speak, the words appear while you're still in the same mental model. The difference sounds small on paper. In practice, it's the difference between flowing and stopping.
It's the same reason Marcus switched to Cursor instead of VS Code. Tab-complete prediction reduces the number of voice rewrites he needs. Every small reduction in cognitive friction compounds across a night of work on a design doc or incident postmortem.
The New Workflow Demands More Words
Incident postmortems used to be written asynchronously, thought through first, then typed. Now they're explained live. Someone asks "what went down" in a Slack thread and you talk through the cascade of events while you're still close to the problem. You need to hold the entire mental model in your head and articulate it. That takes time and that takes words.
The same shift happened to design docs. You're not sketching in Figma and then writing a brief. You're explaining the entire system; why you built it this way, what you optimized for, what you didn't, what the trade-offs are; because the model on the other end needs the full context.
That's the new job. Explaining, not documenting. Speaking clearly enough that the intent is unmistakable. That's where voice wins. You can talk faster than you can type, and you can hold more of the model in your head while you're talking because you're not managing the keyboard.
A word cap in the middle of that is death.
Who This Matters For
This matters if you're explaining code in text more than you're writing it. If your Slack threads are long. If you've hit a word limit mid-thought and had to split your thinking across two dictations. If you're skeptical of cloud transcription because your codebase is proprietary and you've read the terms-of-service carefully. If you work in Cursor and you've noticed Copilot can't always predict what you mean, so you end up dictating the spec anyway.
It matters if you value local-first tools and you don't trust vague privacy policies. It matters if you've experienced the frustration of a word meter becoming the constraint instead of your thinking.
The moment you hit a limit is the moment you lose the thought. Recitey is built so you never have to hit it.