Marcus works on payment settlement at a Series B fintech in Stockholm. Last Wednesday at 11pm, he was dictating a design doc into his laptop, explaining a complex state machine to his team. Three minutes in, his voice transcription tool hit its daily word limit.
He had to stop mid-thought.
The reset your software engineer's brain goes through when you're describing a system out loud is different from writing it down. You explain the flow. You catch edge cases by talking through them. You stumble on problems in the architecture before they're written down. Stop in the middle of that process, and you lose the thread entirely. You finish the doc the next morning, and it reads fragmented, like two people wrote it.
This is a different problem than developers had five years ago. It's not "how do we type code faster." It's "how do we explain intent faster when the code itself comes from the model."
The shift happened quietly
Developers still type code. But their workflow changed. They type intent now. They type specifications into Cursor. They describe bugs in GitHub issues. They write Slack threads that explain investigation findings. They dictate design docs at night because it's the only way to keep the thinking intact.
The bottleneck moved. It's not your hands on the keyboard anymore. It's how fast you can externalize what's in your head before you forget it.
Voice is faster for that. It's not faster at transcription speed. It's faster at thinking out loud. It's faster at the uninterrupted flow state where the hard part of the work actually happens.
Where cloud transcription breaks
Wispr costs $14 a month. Superwhisper costs $8.49 as a one-time buy. Both cap your free tier. Wispr caps you at 600 words per month. Superwhisper caps you at 3 minutes per day. If you hit the cap mid-thought, you're done.
The cap isn't a technical limit. It's a pricing strategy. Cloud transcription has variable costs; you send audio to a server, that server processes it, you pay per use. So the company adds a word counter. They make you feel the friction. That friction converts you to paid.
It's predictable business logic. It's also terrible UX for the new developer workflow.
Marcus tried Wispr for two weeks. He hit the cap on his third design doc. He switched back to typing, lost 20 minutes to prose cleanup the next morning, and decided voice transcription wasn't worth it. He didn't have a transcription problem. He had a workflow problem. He needed to think out loud without hitting a wall.
Why local changes everything
Recitey runs Whisper locally on your device. The speech-to-text model sits on your machine. There's no server call, no queue, no usage tracking, no variable cost per word.
Local processing changes the pricing model entirely. If there's no variable cost, there's no reason for a word cap. No reason for a word counter. No reason to meter the user at all.
The free tier is uncapped. You can dictate 100,000 words a month if you want. Your device processes it. Recitey doesn't see it. It doesn't cost them anything to let you have it.
This is why the free tier isn't a loss leader or a limited trial. It's the actual product for developers who need local processing. The paid tier solves a different problem: cloud-based rewrite. If you want Recitey to polish your rough draft into clean prose using a frontier model, that's when you're sending to their server. But the core dictation is always free and always uncapped.
The IP reason developers care
Marcus refuses to use cloud transcription for another reason: code and design IP.
When you dictate a design doc that explains your payment settlement system into a cloud service, that audio file gets sent to someone else's server. It gets transcribed there. It might get logged, indexed, used for model training, kept for "safety review." Most SaaS terms say they won't, but they're vague enough that you can't be sure. Marcus doesn't want to find out the hard way.
Local processing is the only way to keep sensitive architecture, design decisions, and code details on the device. No upload. No exposure. This is standard practice for any team working in fintech, healthcare, defense, or with proprietary systems. It's table stakes.
And it's why Wispr's cloud-only architecture doesn't work for Marcus's team, even if the word cap didn't exist.
Recitey's local-first design solves both problems at once: no word cap because there's no variable cost to support it, and no data leaving your device because speech-to-text never touches a server.
What this means for the actual workflow
Marcus's design docs are uninterrupted now. He explains the state machine. He catches the edge case. He writes it down. He doesn't hit a cap at minute three and lose the thread.
He switched to Cursor instead of VS Code specifically because Cursor's tab-complete reduces the number of voice rewrites he needs. When you dictate a spec and the model fills in the next sentence based on context, it saves you from over-explaining. Local Whisper works the same way, no bottleneck, no friction point where the system says "sorry, you've used this up."
The free tier is the real product for developers with this workflow. The cloud polish is a feature for people who want it, but the core insight is this: if you're explaining intent to a model, and the model is generating the output, then your bottleneck is how fast and clearly you can externalize the thought. Voice wins there. But only if it's truly uncapped, and only if it stays on your device.