# Build brief — a focused alternative to Wispr Flow

> **Verdict:** Yes, for personal use · **Buildability:** 76/100 · **Category:** Voice Dictation
> **Source:** https://www.canitbevibecoded.com/wispr-flow
> Independent editorial assessment from Can It Be Vibe Coded? Not affiliated with, endorsed by, or derived from Wispr Flow. Verify current pricing and capabilities before acting.

## Context

**Wispr Flow** — Hotkey → record → Whisper → paste at cursor. It currently costs $15/mo.

Hotkey → record → Whisper → paste at cursor. One of the most-cloned apps of the trend for a reason.

This brief describes a focused, single-operator replacement for the part of Wispr Flow that is genuinely reproducible. It is deliberately narrower than the product it replaces, and it says so in writing. Build the useful core; do not pretend to have rebuilt the rest.

## What you are building

A focused, single-user version of Wispr Flow's main workflow.

- Build a focused single-user workflow with real persistence, search, and export.
- A responsive interface with real empty, loading, success, and error states.

## Requirements

### Non-functional

- Accessibility: semantic markup, labelled controls, visible focus, and reduced-motion support.
- Security: server-side secrets, validated input, and no credentials in the client bundle.
- Reliability: retries with backoff on external calls, and a clear failure state when a provider is down.
- Portability: the operator can export their data and leave without losing it.

## Implementation brief

Build me a system-wide AI dictation tool like Wispr Flow for macOS. Requirements:

- A background app with a global hotkey (hold-to-talk fn key or a chosen shortcut).
  While held: record the mic. On release: transcribe and paste.
- Transcribe with whisper.cpp locally (small or medium model), or the Groq/OpenAI
  Whisper API if a key exists in .env · pick per a config flag.
- Pipe the raw transcript through an LLM (key in .env) with a short prompt that
  removes filler words, fixes punctuation, and matches casing to dictation style.
- Insert the result at the current cursor position in whatever app has focus
  (simulate keystrokes or use the pasteboard + Cmd-V approach, restoring the
  previous clipboard afterwards).
- Show a tiny floating pill while recording so I know it's live.
- Menu bar toggle for on/off, launch at login, and a settings file for the hotkey.
- No accounts, no telemetry, works offline with the local model.
- README with the Accessibility/Input Monitoring permissions I need to grant.

## Delivery standard

- Inspect the repository first, then write a short implementation plan before writing code.
- Deliver the smallest complete end-to-end workflow first; every primary control must work against persisted data.
- Use real validation and storage; never substitute fake dashboards, decorative controls, hard-coded success states, or mock integrations.
- Include responsive layouts plus genuine empty, loading, success, validation, and failure states.
- Keep secrets server-side in environment variables, provide .env.example, and never commit credentials or user data.
- Add structured logs around every external call and return actionable errors without leaking sensitive details.
- Write unit tests for the core logic and one automated test of the main user journey.
- Finish with a README covering setup, architecture, data location, backups, tests, deployment, and known limitations.

## Acceptance criteria

- [ ] A clean install starts the app using only the README and .env.example.
- [ ] The primary journey works from first visit through saved result, reload, edit, export, and deletion where applicable.
- [ ] Invalid input, missing configuration, provider failure, and an empty database each have a usable state.
- [ ] The interface works at 390px and 1440px, is keyboard navigable, and shows visible focus on every control.
- [ ] Tests, type checking, linting, and a production build all pass with no ignored failures.
- [ ] No part of the interface implies a live integration, security guarantee, or scale capability that was not actually built and verified.

## Non-goals

Do not build these, and do not claim to have replaced them:

- Their tuned auto-editing voice model.
- Per-app tone formatting.
- The mobile keyboard.
- Polish on edge cases (accents, noise).
- Model quality and inference operations are part of the product.
- The last 20 percent is sync, migration fidelity, speed, and edge cases.

## What you still own after launch

- Run migrations, backups, restores, and dependency updates.
- Test the critical journey after every model, API, or hosting change.
- Monitor failures and fix the edge cases a first prompt will miss.

## Risk

**Manageable.** A personal version is realistic if you test the critical journey and keep reliable backups.

Editorial confidence in this assessment: high. No independent one-shot implementation is linked yet.

## Prior art

Working open-source software you can read, fork, or borrow from before starting:

- [whisper.cpp](https://github.com/ggml-org/whisper.cpp) — local transcription engine
- [VoiceInk](https://github.com/Beingpax/VoiceInk) — open-source macOS dictation app

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Generated by [Can It Be Vibe Coded?](https://www.canitbevibecoded.com) · Full report: https://www.canitbevibecoded.com/wispr-flow