How to vibe codeSupernormal
AI agent platform to turn meetings into completed client work
supernormal.com ↗AI Meeting Assistant & Agent Suite
The verdict: can you vibe code Supernormal?
Build a personal web-based clone with file uploads and LLM template generation, but skip native system audio capture unless you enjoy debugging low-level OS kernel extensions.
Supernormal combines a standard web application dashboard with a brutally hard native desktop utility that hooks into local audio cards without meeting bots. While you can easily vibecode the Next.js web application, rich text notes, project folders, and LLM prompt templates using Claude Code and Cursor, reproducing the native macOS/Windows system-audio capture driver and real-time speaker separation requires deep platform-specific low-level systems programming that AI agents will struggle to scaffold reliably.
Estimated effort: 4-6 weeks of part-time work
What you can't replicate
- Native kernel-level audio capture drivers operating across macOS and Windows without bot injection
- Enterprise trust, SOC 2 Type II compliance, and HIPAA certifications
- The massive active user base and institutional backing network
Founded
2020
Raised
$12.9M
Team
20-35
Cheapest paid tier
$0
What Supernormal does
Supernormal provides bot-free desktop recording for meetings and leverages AI agents to transform unstructured meeting transcripts and context into rich client deliverables such as presentations, documents, spreadsheets, and MCP context feeds.
Core features
- Cross-platform desktop native wrapper (macOS menu bar / Windows taskbar) for local audio capture
- Bot-free audio recording with mic switching and dynamic audio device routing
- Speech-to-text transcription with speaker diarization
- Post-meeting command center with rich-text editor (Notion-style)
- Multi-step AI agent task orchestration for structured artifact generation (presentations, docs, spreadsheets, images)
- Project folders organizing multiple meetings and documents into shared context
- Model Context Protocol (MCP) server integration to feed meeting context into external AI tools (Claude, Cursor)
- Shortcuts and prompt templates for instant summaries and deliverables
The business
Pricing
- Free$0
- Team$0 base tier structure
- BusinessCustom
Funding
$12.9M from EQT Ventures, Balderton Capital, byFounders, Acequia Capital
Pay vs build, cumulative
Break-even at month 1 — after that, every month is money kept.
The hard parts of vibe coding Supernormal
- Capturing system audio and microphone feeds natively across macOS (Apple Silicon kernel/audio extension permissions) and Windows 11 without injecting a virtual calendar bot
- Orchestrating multi-step LLM generations that reliably build complex structured assets (like multi-page presentation decks or spreadsheets) without hallucinations
- Real-time speech transcription pipelines with clean speaker diarization and audio buffering during device switches
How to vibecode Supernormal
Prerequisites
Node.jsfree
Runtime for running Next.js web application and build scripts.
GitHubfree
Version control and repository hosting for your codebase.
AI coding tools
Recommended stack
| Frontend | Next.js with Tailwind CSS and shadcn/ui components |
|---|---|
| Backend | Next.js API routes / Server Actions |
| Database | Turso (libSQL/SQLite at the edge) |
| Auth | better-auth |
| Payments | none |
| Other | Vercel AI SDK, OpenAI API (Whisper STT + GPT), Anthropic API (Claude Sonnet for agentic generation) |
Build guide
01Project Scaffolding and Database Schema
Initialize the Next.js project with Tailwind CSS, shadcn/ui, Turso connection via Drizzle ORM, and better-auth for single-user management.
Scrape together a new Next.js project using Tailwind CSS and TypeScript. Set up Turso database connectivity using Drizzle ORM with tables for 'users', 'projects', 'meetings' (storing title, transcript, raw audio URL, status, and summary), and 'deliverables' (storing type, content, and metadata). Configure better-auth for local user authentication. Ensure all configuration files are complete and clean.02Audio Upload and Transcription Pipeline
Build an audio file upload interface in the web app and connect it to OpenAI's Whisper API for batch transcription and speaker diarization.
Create a meeting capture upload page in Next.js where users can drag and drop audio recordings (.mp3, .wav, .m4a). Implement a server action that uploads the file to object storage and calls the OpenAI Whisper API to get the transcript with timestamps and speaker tags. Save the resulting transcript JSON directly to the Turso meetings table.03Rich Text Meeting Notes and Project Folders
Develop the post-meeting dashboard featuring a Notion-style rich text editor for notes and project grouping drawers.
Build a post-meeting workspace page using Tailwind CSS with a split-pane layout. The left side features a rich-text markdown editor for meeting notes that auto-saves changes to the backend. The right side contains a collapsible AI chat and shortcuts panel. Add a Projects management view that allows grouping multiple meetings into a shared project container.04Agentic Deliverable Generation
Implement Vercel AI SDK integrations to let AI agents generate structured deliverables (presentations, briefs, one-pagers) from meeting context.
Integrate the Vercel AI SDK with Anthropic Claude Sonnet to power an agentic generator. Create template actions that ingest a meeting's transcript and project notes to output structured JSON representations of slide decks, creative briefs, or budgets. Build a UI renderer that displays these generated artifacts inside the workspace and allows exporting them.05Model Context Protocol (MCP) Server Integration
Expose an MCP endpoint or local server config so external developer tools like Cursor and Claude Desktop can read meeting history and context.
Implement an MCP (Model Context Protocol) server route within the Next.js backend that exposes tools to query past meeting notes, transcripts, and project summaries by keyword or project ID. Include setup instructions and a configuration payload snippet for connecting Claude Desktop or Cursor to your local MCP server.
Cost vs paying for Supernormal
What will you build it with?
Starting total with Claude Code$0 one-time
Starting costs (one-time)
- Domain name registration$12 one-time
- OpenAI/Anthropic API starter credits$10 one-time
Total~$22 one-time
Ongoing costs (monthly)
- Vercel Hobby / Turso / Cloudflare R2$0/mo
- OpenAI Whisper & Claude API usage (personal volume)~$5/mo
Total~$5/mo
Paying for Supernormal
~$18-50/mo
Your time to build
40-60 hours
AI tool credits
$20 (Claude Pro or Cursor Pro)
Break-even
N/A (Personal clone)
Vibe code Supernormal: FAQ
- Can you vibe code Supernormal yourself?
- Serious undertaking — 35/100 vibecodeable. Build a personal web-based clone with file uploads and LLM template generation, but skip native system audio capture unless you enjoy debugging low-level OS kernel extensions.
- How long does it take to vibe code Supernormal?
- 4-6 weeks of part-time work — roughly 40-60 hours of hands-on time with an AI coding agent.
- How do you build your own Supernormal?
- Scoped to personal use: Next.js with Tailwind CSS and shadcn/ui components on the front, Next.js API routes / Server Actions behind it, Turso (libSQL/SQLite at the edge) for data. Follow the 5-step build guide on this page — each step has a paste-ready prompt for an AI coding agent.
- How do you code your own Supernormal without being an expert?
- Use an AI coding tool (Claude Code or Cursor) and work in small steps: scaffold, data model, core screens, then deploy. Realistic effort: 4-6 weeks of part-time work. The prompts on this page are written so the AI does the heavy lifting.
- How much does it cost to vibe code Supernormal instead of paying?
- About ~$22 one-time to start and ~$5/mo to run, versus ~$18-50/mo for Supernormal. Break-even: N/A (Personal clone).
- What stack should you use to vibe code Supernormal?
- Next.js with Tailwind CSS and shadcn/ui components; Next.js API routes / Server Actions; Turso (libSQL/SQLite at the edge); plus Vercel AI SDK, OpenAI API (Whisper STT + GPT), Anthropic API (Claude Sonnet for agentic generation).