You're explaining a complex bug in a Slack thread. You explain it perfectly on the call, then spend 12 minutes rewriting the follow-up because you hit a word cap at 600 words on your dictation tool's free tier.
This is the constraint that shapes most speech-to-text tools: cloud transcription costs money per minute. So vendors cap the free tier hard. Wispr Flow stops at 600 words/month, Willow at 1000, Superwhisper at 500. Once you're out, you buy.
But the constraint is wrong for what developers actually do with voice.
The Workflow Changed, the Tools Didn't
Cursor runs on your laptop. Claude Code runs on your laptop. GitHub Copilot knows your codebase. The bottleneck moved from "how fast can you type code" to "how clearly can you explain what the model should build."
A design doc for a payment settlement system. A Slack thread that traces a production outage from the client error backward through your logs. A PR comment explaining why you rejected a suggestion. A postmortem that captures the decision cascade that led to the incident.
These aren't notes. They're specifications. They're long.
And they're written at odd hours, when the thinking is hot. 11pm. 2am. The moment after a deploy at 9pm when you're still context-loaded and you're writing 2000 words of incident postmortem because you want to get it right.
Cloud word limits were built for a different use case: quick voice memos, voice-to-text in the field, transcribing meetings. Not for specifying what an LLM should build.
Why Local Whisper Changes Everything
Whisper, OpenAI's speech-to-text model, runs on your device. Your words never leave your laptop. The transcription cost is zero. You can dictate 10,000 words at 2am. No counter. No cap. No paywall.
Recitey uses Whisper locally on your device with zero variable cost. The free tier is uncapped. You get the speech-to-text part, rough transcription from voice, without the metering.
The cloud-based tools transcribe too. Otter.ai transcribes to text, then sells you the clean version. Wispr Flow transcribes, then charges you when you run out of words. That architecture made sense when speech-to-text was hard. But Whisper hit 96.3% word accuracy on LibriSpeech, the accuracy ceiling. Running locally isn't a tradeoff anymore. It's just faster and cheaper.
The reason cloud tools still gate free tier is distribution cost, not technology cost. They need to funnel you to paid. Once you've restructured your workflow around them, you renew.
Local-first tools don't have that motive.
What Changes After You Stop Hitting the Limit
Marcus is a backend engineer on a Series B fintech. He dictates design docs in Cursor. His rough Whisper transcription lands in a buffer window. He reads it, fixes the obvious mistakes. Whisper sometimes translates "OAuth" to "oh auth". Within 20 seconds he's got clean prose.
He used to hit caps. He'd abandon a design doc halfway, write a short note instead, then reconstruct the full thought the next morning when he was context-switched out.
Now he doesn't think about the word counter. He's writing 3000 words of design doc in one voice session. He's drafting a Slack thread explaining a payment settlement bug in one pass. He's describing the PR intent in full detail instead of leaving the review comment half-finished.
The word counter disappears from his mental model. The friction you didn't know you had (should I voice this or type it) goes away.
There's a secondary shift: precision. Whisper makes mistakes. "OAuth" becomes "oh auth". "Cursor" becomes "coerce." When you hit the word limit, you're also rushing to edit. When the limit's gone, you read the rough transcription calmly and fix the real errors. The prose gets better, not worse.
The Trade-Off: Rewrite Still Exists
Local Whisper isn't perfect. It's rough. You'll read the transcription and see "coerce" where you said "Cursor". You'll see "oh auth" where you said "OAuth".
The free tier gives you that rough transcription. It doesn't give you the cloud rewrite that Wispr or Otter polish the text into a finished sentence.
Recitey's Pro tier adds that cloud-side rewrite. You speak, you see the rough local transcription, then you ask for the polish pass, and it comes back in under 2 seconds.
But the point is: you're not paying for transcription. You're paying for the cleanup. The transcription was already free.
And if you're writing 2000-word design docs and 600-word Slack threads, the rough Whisper is usually good enough to catch on a quick read. The rewrite is optional.
Who Should Use This (And Who Shouldn't)
If you spend 30 minutes a week or more writing intent, design docs, explanations, specs, PR comments, postmortems, Slack threads explaining production bugs, then uncapped speech-to-text is a constraint-breaker.
If you dictate to-do lists and voice memos, you probably don't care about word limits.
If you use Dragon NaturallySpeaking for transcription meetings, you've already paid $300 upfront. That's a different product for a different use case.
If you've built your workflow around Wispr or Otter, switching is a small friction. They're good tools. But if you're choosing now, and you're skeptical of word limits by design, try the local version first.