Marcus hit the wall at 3,247 words. He was mid-thought on payment settlement logic, speaking into Wispr, and the free tier capped out. The thinking wasn't done. The architecture wasn't written. He had to switch to typing, fragment the idea into a Slack thread, and finish the doc the next morning. By then, the flow was gone.
This isn't a typing-speed problem. This is a prompt-writing problem.
How the workflow actually shifted
Most voice tools still market themselves to writers and note-takers. They're designed for people who type a lot and want to type less. But developers working with Claude Code or Cursor aren't typing code anymore, they're typing intent. Prompts. Specifications. The bottleneck moved.
A backend engineer now spends more time writing "here's what I need this payment reconciliation service to do" than writing the reconciliation service itself. That's 800 words of careful thinking. That's context. That's workflow explanation. That's code intent that no LLM will guess from a fragment.
And when you hit a word cap mid-thought, you lose the architecture.
The technical reality of word limits
Wispr's free tier caps at 2,000 words per day. Superwhisper costs $8.49 per month and meters usage. Willow's free tier has the same cap. All of them assume you're transcribing short memos or quick notes.
None of them assume you're dictating a 900-word design doc at 11pm because that's when the architecture clarified itself.
The reason they meter is the same reason most SaaS pricing feels high: the cloud backend costs money to run. Every transcription spins up a server, sends audio somewhere, waits for a response. That's variable cost. That's why there's a cap.
Recitey runs Whisper locally on your device. No audio leaves. No cloud round-trip. Zero variable cost for the dictation itself. Your machine does the work. The word count is infinite because there's no meter to justify.
Why this matters for code context
Marcus refuses to use cloud transcription for another reason beyond pricing. He's dictating design docs that mention client names, payment logic, settlement flows, database schemas. That audio shouldn't travel through someone else's infrastructure. Local processing means the code stays on the device.
It's not paranoia. It's the difference between "we're using Google Dictation, I'm OK with that" versus "this is a fintech codebase and I don't need to explain to legal why voice data left the building."
You can't see the backend of most voice tools. You can't verify where the audio goes. If the tool won't tell you, it's hiding something.
The trade-off is real
Local-first means no cloud features. No speaker identification. No real-time correction. No integration with every third-party service. You don't get the polish of Whisper cloud running on Superwhisper's servers. You get Whisper on your machine, working in Slack, email, Cursor, GitHub, Notion, the browser, anywhere you paste text.
It's simpler. It's slower to improve. It's also private and uncapped.
Most developers choosing between "fast cloud with a word limit" and "local with no limit" will choose the one that doesn't interrupt their thinking. Especially at 11pm when the architecture finally clicked and the design doc needs to exist before tomorrow morning.
Who this is actually for
This isn't for people who want to dictate Slack messages faster. It's for engineers working with LLM workflows who've realized that explaining what you want built takes more words than the old contract said you'd ever need. It's for people who switched to Cursor from VS Code specifically because tab-complete reduces rewrites, and who won't use cloud tools with code IP concerns.
If your bottleneck is prompt articulation, not typing speed, and you're on Windows, the word cap was always someone else's problem.