The shift to prompt-driven development changed what "good documentation" actually means. When you're explaining intent to Claude or Cursor, not just recording decisions for people, the prose gets longer. More precise. More conditional. It needs to sound like a specification, not a summary.
This is where the voice tool gap opens up. Most premium dictation tools meter the free tier by word count. The cap exists to push you toward paid. But for the new workflow, it hits exactly where it shouldn't.
The actual bottleneck moved
Marcus works on payment settlement at a Series B fintech in Stockholm. His day is Cursor, Slack, code review, incident postmortems. At 11pm mid-sprint, he's working in Notion on an async job queue design. His thinking's flowing. He's 400 words in, explaining error handling, edge cases, why the original approach won't scale. He switches to voice to keep the thread alive, faster than typing the nuance.
At 650 words, the tool stops. Word limit hit. Two options: switch back to typing (flow broken), or split the thought across documents (doesn't make sense). He picks typing. The moment's lost. Rest of the doc's fragmented, less precise, less useful to his team.
This happens because most voice tools price as if dictation's value is typing-speed. But in 2026, for teams using Claude and Copilot, it's thinking-speed: holding the mental model while you articulate it. A word cap breaks that entirely.
Why local-first changes this
Recitey runs Whisper locally on your device. No API calls, no metering, no cap. You speak as long as you think. The transcription layer costs nothing per word. There's no economic incentive to gate it.
For Marcus, this means 11pm design docs flow end-to-end without sending code or architecture to a cloud API. No interruption. The precision that LLM workflows require stays intact.
The trade-off's simple: local transcription is fast (no network latency) but doesn't rewrite your draft into "professional" language like cloud tools do. That's why Recitey's pro tier adds cloud rewrite. Free captures the thought. Pro polishes it. For Marcus, free solves the real problem anyway; he'd rather keep code out of cloud APIs.
Numbers back this up
Whisper-large-v3 hits 96.3% accuracy on LibriSpeech-test-clean. For unscripted speech in technical contexts, real accuracy's usually 92-95%, good enough for spec writing. Accuracy isn't the ceiling. Interruption is.
Most developers in Cursor or Claude Code spend significant time writing prompts and specifications. The shift from code-first to prompt-first means voice tools that interrupt mid-thought are broken by design. They were built for the old workflow.
Who this is for and who it isn't
If you're drafting Slack messages and quick notes, any tool works. If you're writing design docs, specifications, or incident postmortems while your thinking's live, the word cap matters. Tools like Wispr and Willow work fine for messaging. Recitey's built for the 11pm design doc moment, where three minutes of uninterrupted thought produce a page of precise specification.
The idea isn't to win everyone. It's to win the moment where voice's speed should matter most, then not break it.