Your design docs are where your thinking lives. You dictate them at 11pm, explaining complex systems before code review. But every cloud dictation tool interrupts you mid-thought with a word cap.
The moment the tool stops, your flow stops. The prose fragments. Tomorrow morning, you're rewriting.
The Design Doc That Breaks Midway
Marcus is a backend engineer at a fintech in Stockholm. He works on payment settlement. His design docs run long, three to five thousand words per doc. He needs to explain the state machine, the edge cases, the retry logic, the assumptions his team won't catch at first glance.
He's tried Wispr, Superwhisper, and Willow. Every one caps the free tier. None of them run locally. Every word he dictates travels to their servers. For payment settlement code, that's a non-starter. He doesn't want his IP or design reasoning sitting in some tool's logging backend.
So he's been recording his design docs in long snatches, interrupted by tool limits. The thinking continues, but the tool stops. He's learned to time his thoughts around the meter. Which defeats the entire point.
Where Voice Becomes Irreplaceable
Design docs are not prose. They're thinking captured in real-time. The best ones sound like a conversation with someone who understands the problem deeply. When you write them, the voice is flat, careful, hedged. When you dictate them, the voice is alive. It carries confidence, doubt, reasoning, trade-offs. It sounds like someone who's actually built the thing.
Marcus tried typing his last three design docs. The prose was cautious. He hedged every statement. He spent 40% more time revising to add back the confidence that dictation had given him automatically.
Dictation captures the thinking stream. Writing flattens it.
The Moment Whisper Local Changed It
Whisper is OpenAI's speech-to-text model. It's been trained on 680,000 hours of multilingual audio data collected from the web. Its accuracy on English reaches 96.3% on LibriSpeech, an industry standard. For design docs, clear speech from native speakers, it works reliably.
Recitey runs Whisper locally on your machine. No cloud server. No API meter. No variable cost per word. The speech-to-text runs on your CPU while you dictate. You never hit a cap. You never lose your flow.
Marcus switched to local Whisper for his last design doc. Fourteen hundred words, no cap. No interruption. He stayed in the voice, the thinking stream, the confidence. The prose was cleaner. The review went faster. His team caught half as many questions during review, because the thinking was clear.
What Actually Changes
When you remove the cap, what changes?
The obvious: you can finish the thought.
The less obvious: you stop anticipating the cap. You don't ration your thinking. You don't pre-edit yourself to fit the meter. You don't interrupt your own explanation because you're worried about hitting a limit.
The writing breathes. It sounds like someone thinking, not someone optimizing for word count.
Marcus realized he'd been writing differently just by knowing the cap was there. He'd broken complex ideas into smaller chunks. He'd shortened explanations. He'd removed the nuance because nuance is verbose. The cap was shaping his thinking before he even started dictating.
Without it, the thinking expanded. The explanations deepened. The edge cases got their due.
The Trade-off That Isn't
You might expect: local Whisper costs something. Latency, accuracy, privacy risk, vendor lock-in.
Latency: local is faster. Whisper runs on your machine while you speak. No network round-trip.
Accuracy: 96.3% on LibriSpeech. Same model, same accuracy, same language support. Same drafting workflow in Cursor, same tab-complete for cleanup.
Privacy: nothing leaves your machine. No cloud logging. No vendor seeing your IP.
Vendor lock-in: Whisper is open source. The model is yours. The data stays yours.
The actual trade-off: local Whisper doesn't rewrite your drafts for you. It transcribes cleanly, but it doesn't punch up the prose or fix the grammar. That's the Pro feature in other tools. But for design docs, for explaining thinking, clean transcription is usually enough. The prose is meant to sound like a human explaining something complex, not like a polished marketing artifact.
Marcus uses Cursor for cleanup. Tab-complete finishes the thought. He refines in under two minutes. The prose stays in his voice, not in some rewriting algorithm's voice.
Who This Is For
If you're designing systems at 11pm, explaining code on calls, writing long-form intent for your team: you probably know the moment when the cap interrupts. Local Whisper is for developers who want to finish the thought without the meter.