Voice-First Coding: How Typeless Changed My Vibe Coding Workflow

There's a term floating around dev circles lately: vibe coding. The idea is simple — instead of writing code character by character, you describe what you want in natural language and let AI generate it. You're coding by vibes, not by syntax.

I've been vibe coding for about six months now, using tools like Cursor, GitHub Copilot, and Claude. And here's what I realized after the first month: vibe coding is fundamentally about talking to your computer. So why was I still typing to it?

That question led me to Typeless, an AI-powered voice dictation tool. It completely changed how I interact with AI coding assistants. This is the story of that shift.

What Vibe Coding Actually Looks Like

If you haven't tried vibe coding yet, here's the basic loop:

1. You describe what you want in plain English (or whatever language you think in)
2. An AI assistant generates the code
3. You review, tweak, and iterate
4. Repeat

The "describe what you want" step is where most of the creative work happens. You're essentially being a product manager and architect at the same time, translating requirements into clear descriptions that an AI can act on.

And that description step? It's writing. A lot of writing. Not code — English. Paragraphs of context, requirements, constraints, and preferences.

Here's a real example from last week. I needed to add a caching layer to an API client:

"Add a caching layer to the API client in src/services/api.ts. Use a simple in-memory cache with TTL support. The cache key should be based on the endpoint URL and query parameters. Default TTL should be 5 minutes but configurable per endpoint. GET requests only — don't cache POST, PUT, or DELETE. Add a cache invalidation method that accepts a pattern to clear matching keys. Make sure it's thread-safe for concurrent requests to the same endpoint — use a promise-based deduplication pattern so we don't fire duplicate requests while one is in flight."

That's 95 words. At my typing speed of about 70 WPM, that's roughly 80 seconds of typing. Speaking it with Typeless? About 35 seconds. And — this is the important part — the spoken version was actually more detailed than what I would have typed, because typing that much feels like effort while speaking it feels like just... explaining what I want.

Why Voice Is Natural for Vibe Coding

Think about how you explain a coding problem to a colleague. You don't type it out — you talk through it. "So basically, we need this thing to check if the user has permission, and if they do, fetch their data from the cache first, and if it's not in the cache, hit the database, but we need to handle the case where their permissions changed since the cache was populated..."

That's exactly what vibe coding prompts sound like. They're conversational explanations of what you want the code to do. Voice dictation just removes the translation step between thinking and input.

Typeless handles this particularly well because it understands technical vocabulary. When I say "API endpoint," it doesn't write "a p.i. end point." When I say "async await," it gets it right. When I mention specific function names or file paths, the accuracy is solid enough that I rarely need corrections.

My Voice-First Vibe Coding Setup

Here's my actual daily workflow:

Describing Features to Cursor

I use Cursor as my primary editor with AI integration. When I need to build something new, I open the chat panel and dictate my requirements using Typeless. The flow is:

1. Look at the relevant code files to get context
2. Hit the Typeless shortcut to start dictation
3. Describe what I want, referencing specific files, functions, and patterns
4. Review the generated code
5. Dictate follow-up refinements

The refinement step is where voice really shines. Instead of typing "actually, change the error handling to use the custom AppError class and add logging," I just say it. The iteration loop gets much tighter.

Writing Code Comments and Documentation

This surprised me — I write way more comments now. Before Typeless, writing a detailed comment felt like overhead. Now I just narrate what the code does while I'm looking at it:

"This function handles the OAuth callback flow. It validates the authorization code, exchanges it for tokens, creates or updates the user record, and sets up the session. The retry logic on line 45 handles the race condition where two callbacks arrive simultaneously for the same user."

That becomes a perfect block comment. And because I'm explaining rather than writing, the comments end up being clearer and more useful than what I'd type.

PR Descriptions That Don't Suck

We've all written PR descriptions that say "fixed the thing" or "updated styles." With voice dictation, writing a proper PR description takes 30 seconds:

"This PR adds rate limiting to the public API endpoints. I used a sliding window algorithm with Redis as the backing store. The default limit is 100 requests per minute per API key, configurable via environment variables. I also added a rate limit headers middleware so clients can see their remaining quota. The main changes are in the middleware directory — I added a new rate limiter class and updated the router to apply it to all public routes. Tests cover the basic flow plus edge cases around window boundaries and concurrent requests."

That's a genuinely useful PR description, and it took less time than typing "added rate limiting."

Technical Documentation

I've started drafting technical docs by voice too. Architecture decisions, API documentation, onboarding guides — anything that's primarily explanatory text. I dictate a first draft, then clean it up in the editor. The first draft is usually 80% there, which means the editing pass is quick.

The Efficiency Gap Is Real

I tracked my productivity for a month after switching to voice-first vibe coding. Here's what I found:

Prompt writing speed:

• Typing: ~70 WPM effective (including thinking pauses and corrections)
• Voice with Typeless: ~140 WPM effective
• Improvement: roughly 2x faster

Prompt quality (measured by how often the AI got it right on the first try):

• Typed prompts: ~60% first-try success
• Voice prompts: ~75% first-try success
• Why: voice prompts tend to be more detailed and conversational, which gives the AI more context

Overall time per feature (from description to working code):

• Before voice: average 12 minutes for a medium-complexity feature
• After voice: average 8 minutes
• Improvement: ~33% faster

The quality improvement surprised me most. When typing feels like effort, you unconsciously cut corners — shorter descriptions, fewer constraints mentioned, less context provided. When speaking is effortless, you naturally give more detail.

Combining Voice with Code Review Audio

Here's a bonus workflow I stumbled into: using ElevenLabs to read code back to me. I'll have it narrate a code review while I'm doing something else — making lunch, stretching, whatever. Hearing code described out loud catches different issues than reading it visually. It's like having a colleague walk you through their changes.

So the full loop becomes: voice in (Typeless for dictation) → AI generates code → voice out (ElevenLabs for review). It's a surprisingly natural workflow.

Common Objections (And My Responses)

"Won't people in the office hear you?"

I work from home most days, so this isn't an issue for me. But even in an office, you can speak quietly — Typeless picks up low-volume speech well. Also, plenty of people already take calls and have meetings at their desks. Dictating code prompts is no louder than a Zoom call.

"Voice can't handle code syntax."

You're right, and that's not what I use it for. I use voice for the natural language parts — descriptions, prompts, comments, documentation. The actual code is still generated by AI or typed manually. Voice handles the 60% of vibe coding that's English; the keyboard handles the 40% that's syntax.

"What about accuracy?"

Typeless is accurate enough that I correct maybe one word per paragraph. For technical terms it hasn't seen, I'll occasionally need to fix something, but it learns from context quickly. The time saved far outweighs the occasional correction.

Getting Started

If you want to try this workflow:

1. Install Typeless — it works on Mac, Windows, and has mobile support
2. Set up a keyboard shortcut for quick activation
3. Start with low-stakes stuff: code comments, commit messages, PR descriptions
4. Graduate to full prompt dictation once you're comfortable with the accuracy
5. Try ElevenLabs for the audio review loop if you want the full voice-first experience

The key insight is this: vibe coding is already "talking to your computer." Voice dictation just makes that literal instead of metaphorical. Once you make the switch, typing out long prompts feels like an unnecessary bottleneck.

Vibe coding's promise was always that you could describe what you want and get working code. Voice dictation is the missing piece that makes that description step as fast as thinking.

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